AI is developing all the time. Here are some picks from several articles what is expected to happen in AI and around it in 2025. Here are picks from various articles, the texts are picks from the article edited and in some cases translated for clarity.
AI in 2025: Five Defining Themes
https://news.sap.com/2025/01/ai-in-2025-defining-themes/
Artificial intelligence (AI) is accelerating at an astonishing pace, quickly moving from emerging technologies to impacting how businesses run. From building AI agents to interacting with technology in ways that feel more like a natural conversation, AI technologies are poised to transform how we work.
But what exactly lies ahead?
1. Agentic AI: Goodbye Agent Washing, Welcome Multi-Agent Systems
AI agents are currently in their infancy. While many software vendors are releasing and labeling the first “AI agents” based on simple conversational document search, advanced AI agents that will be able to plan, reason, use tools, collaborate with humans and other agents, and iteratively reflect on progress until they achieve their objective are on the horizon. The year 2025 will see them rapidly evolve and act more autonomously. More specifically, 2025 will see AI agents deployed more readily “under the hood,” driving complex agentic workflows.
In short, AI will handle mundane, high-volume tasks while the value of human judgement, creativity, and quality outcomes will increase.
2. Models: No Context, No Value
Large language models (LLMs) will continue to become a commodity for vanilla generative AI tasks, a trend that has already started. LLMs are drawing on an increasingly tapped pool of public data scraped from the internet. This will only worsen, and companies must learn to adapt their models to unique, content-rich data sources.
We will also see a greater variety of foundation models that fulfill different purposes. Take, for example, physics-informed neural networks (PINNs), which generate outcomes based on predictions grounded in physical reality or robotics. PINNs are set to gain more importance in the job market because they will enable autonomous robots to navigate and execute tasks in the real world.
Models will increasingly become more multimodal, meaning an AI system can process information from various input types.
3. Adoption: From Buzz to Business
While 2024 was all about introducing AI use cases and their value for organizations and individuals alike, 2025 will see the industry’s unprecedented adoption of AI specifically for businesses. More people will understand when and how to use AI, and the technology will mature to the point where it can deal with critical business issues such as managing multi-national complexities. Many companies will also gain practical experience working for the first time through issues like AI-specific legal and data privacy terms (compared to when companies started moving to the cloud 10 years ago), building the foundation for applying the technology to business processes.
4. User Experience: AI Is Becoming the New UI
AI’s next frontier is seamlessly unifying people, data, and processes to amplify business outcomes. In 2025, we will see increased adoption of AI across the workforce as people discover the benefits of humans plus AI.
This means disrupting the classical user experience from system-led interactions to intent-based, people-led conversations with AI acting in the background. AI copilots will become the new UI for engaging with a system, making software more accessible and easier for people. AI won’t be limited to one app; it might even replace them one day. With AI, frontend, backend, browser, and apps are blurring. This is like giving your AI “arms, legs, and eyes.”
5. Regulation: Innovate, Then Regulate
It’s fair to say that governments worldwide are struggling to keep pace with the rapid advancements in AI technology and to develop meaningful regulatory frameworks that set appropriate guardrails for AI without compromising innovation.
12 AI predictions for 2025
This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.
https://www.cio.com/article/3630070/12-ai-predictions-for-2025.html
This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.
1. Small language models and edge computing
Most of the attention this year and last has been on the big language models — specifically on ChatGPT in its various permutations, as well as competitors like Anthropic’s Claude and Meta’s Llama models. But for many business use cases, LLMs are overkill and are too expensive, and too slow, for practical use.
“Looking ahead to 2025, I expect small language models, specifically custom models, to become a more common solution for many businesses,”
2. AI will approach human reasoning ability
In mid-September, OpenAI released a new series of models that thinks through problems much like a person would, it claims. The company says it can achieve PhD-level performance in challenging benchmark tests in physics, chemistry, and biology. For example, the previous best model, GPT-4o, could only solve 13% of the problems on the International Mathematics Olympiad, while the new reasoning model solved 83%.
If AI can reason better, then it will make it possible for AI agents to understand our intent, translate that into a series of steps, and do things on our behalf, says Gartner analyst Arun Chandrasekaran. “Reasoning also helps us use AI as more of a decision support system,”
3. Massive growth in proven use cases
This year, we’ve seen some use cases proven to have ROI, says Monteiro. In 2025, those use cases will see massive adoption, especially if the AI technology is integrated into the software platforms that companies are already using, making it very simple to adopt.
“The fields of customer service, marketing, and customer development are going to see massive adoption,”
4. The evolution of agile development
The agile manifesto was released in 2001 and, since then, the development philosophy has steadily gained over the previous waterfall style of software development.
“For the last 15 years or so, it’s been the de-facto standard for how modern software development works,”
5. Increased regulation
At the end of September, California governor Gavin Newsom signed a law requiring gen AI developers to disclose the data they used to train their systems, which applies to developers who make gen AI systems publicly available to Californians. Developers must comply by the start of 2026.
There are also regulations about the use of deep fakes, facial recognition, and more. The most comprehensive law, the EU’s AI Act, which went into effect last summer, is also something that companies will have to comply with starting in mid-2026, so, again, 2025 is the year when they will need to get ready.
6. AI will become accessible and ubiquitous
With gen AI, people are still at the stage of trying to figure out what gen AI is, how it works, and how to use it.
“There’s going to be a lot less of that,” he says. But gen AI will become ubiquitous and seamlessly woven into workflows, the way the internet is today.
7. Agents will begin replacing services
Software has evolved from big, monolithic systems running on mainframes, to desktop apps, to distributed, service-based architectures, web applications, and mobile apps. Now, it will evolve again, says Malhotra. “Agents are the next phase,” he says. Agents can be more loosely coupled than services, making these architectures more flexible, resilient and smart. And that will bring with it a completely new stack of tools and development processes.
8. The rise of agentic assistants
In addition to agents replacing software components, we’ll also see the rise of agentic assistants, adds Malhotra. Take for example that task of keeping up with regulations.
Today, consultants get continuing education to stay abreast of new laws, or reach out to colleagues who are already experts in them. It takes time for the new knowledge to disseminate and be fully absorbed by employees.
“But an AI agent can be instantly updated to ensure that all our work is compliant with the new laws,” says Malhotra. “This isn’t science fiction.”
9. Multi-agent systems
Sure, AI agents are interesting. But things are going to get really interesting when agents start talking to each other, says Babak Hodjat, CTO of AI at Cognizant. It won’t happen overnight, of course, and companies will need to be careful that these agentic systems don’t go off the rails.
Companies such as Sailes and Salesforce are already developing multi-agent workflows.
10. Multi-modal AI
Humans and the companies we build are multi-modal. We read and write text, we speak and listen, we see and we draw. And we do all these things through time, so we understand that some things come before other things. Today’s AI models are, for the most part, fragmentary. One can create images, another can only handle text, and some recent ones can understand or produce video.
11. Multi-model routing
Not to be confused with multi-modal AI, multi-modal routing is when companies use more than one LLM to power their gen AI applications. Different AI models are better at different things, and some are cheaper than others, or have lower latency. And then there’s the matter of having all your eggs in one basket.
“A number of CIOs I’ve spoken with recently are thinking about the old ERP days of vendor lock,” says Brett Barton, global AI practice leader at Unisys. “And it’s top of mind for many as they look at their application portfolio, specifically as it relates to cloud and AI capabilities.”
Diversifying away from using just a single model for all use cases means a company is less dependent on any one provider and can be more flexible as circumstances change.
12. Mass customization of enterprise software
Today, only the largest companies, with the deepest pockets, get to have custom software developed specifically for them. It’s just not economically feasible to build large systems for small use cases.
“Right now, people are all using the same version of Teams or Slack or what have you,” says Ernst & Young’s Malhotra. “Microsoft can’t make a custom version just for me.” But once AI begins to accelerate the speed of software development while reducing costs, it starts to become much more feasible.
9 IT resolutions for 2025
https://www.cio.com/article/3629833/9-it-resolutions-for-2025.html
1. Innovate
“We’re embracing innovation,”
2. Double down on harnessing the power of AI
Not surprisingly, getting more out of AI is top of mind for many CIOs.
“I am excited about the potential of generative AI, particularly in the security space,”
3. And ensure effective and secure AI rollouts
“AI is everywhere, and while its benefits are extensive, implementing it effectively across a corporation presents challenges. Balancing the rollout with proper training, adoption, and careful measurement of costs and benefits is essential, particularly while securing company assets in tandem,”
4. Focus on responsible AI
The possibilities of AI grow by the day — but so do the risks.
“My resolution is to mature in our execution of responsible AI,”
“AI is the new gold and in order to truly maximize it’s potential, we must first have the proper guardrails in place. Taking a human-first approach to AI will help ensure our state can maintain ethics while taking advantage of the new AI innovations.”
5. Deliver value from generative AI
As organizations move from experimenting and testing generative AI use cases, they’re looking for gen AI to deliver real business value.
“As we go into 2025, we’ll continue to see the evolution of gen AI. But it’s no longer about just standing it up. It’s more about optimizing and maximizing the value we’re getting out of gen AI,”
6. Empower global talent
Although harnessing AI is a top objective for Morgan Stanley’s Wetmur, she says she’s equally committed to harnessing the power of people.
7. Create a wholistic learning culture
Wetmur has another talent-related objective: to create a learning culture — not just in her own department but across all divisions.
8. Deliver better digital experiences
Deltek’s Cilsick has her sights set on improving her company’s digital employee experience, believing that a better DEX will yield benefits in multiple ways.
Cilsick says she first wants to bring in new technologies and automation to “make things as easy as possible,” mirroring the digital experiences most workers have when using consumer technologies.
“It’s really about leveraging tech to make sure [employees] are more efficient and productive,”
“In 2025 my primary focus as CIO will be on transforming operational efficiency, maximizing business productivity, and enhancing employee experiences,”
9. Position the company for long-term success
Lieberman wants to look beyond 2025, saying another resolution for the year is “to develop a longer-term view of our technology roadmap so that we can strategically decide where to invest our resources.”
“My resolutions for 2025 reflect the evolving needs of our organization, the opportunities presented by AI and emerging technologies, and the necessity to balance innovation with operational efficiency,”
Lieberman aims to develop AI capabilities to automate routine tasks.
“Bots will handle common inquiries ranging from sales account summaries to HR benefits, reducing response times and freeing up resources for strategic initiatives,”
Not just hype — here are real-world use cases for AI agents
https://venturebeat.com/ai/not-just-hype-here-are-real-world-use-cases-for-ai-agents/
Just seven or eight months ago, when a customer called in to or emailed Baca Systems with a service question, a human agent handling the query would begin searching for similar cases in the system and analyzing technical documents.
This process would take roughly five to seven minutes; then the agent could offer the “first meaningful response” and finally begin troubleshooting.
But now, with AI agents powered by Salesforce, that time has been shortened to as few as five to 10 seconds.
Now, instead of having to sift through databases for previous customer calls and similar cases, human reps can ask the AI agent to find the relevant information. The AI runs in the background and allows humans to respond right away, Russo noted.
AI can serve as a sales development representative (SDR) to send out general inquires and emails, have a back-and-forth dialogue, then pass the prospect to a member of the sales team, Russo explained.
But once the company implements Salesforce’s Agentforce, a customer needing to modify an order will be able to communicate their needs with AI in natural language, and the AI agent will automatically make adjustments. When more complex issues come up — such as a reconfiguration of an order or an all-out venue change — the AI agent will quickly push the matter up to a human rep.
Open Source in 2025: Strap In, Disruption Straight Ahead
Look for new tensions to arise in the New Year over licensing, the open source AI definition, security and compliance, and how to pay volunteer maintainers.
https://thenewstack.io/open-source-in-2025-strap-in-disruption-straight-ahead/
The trend of widely used open source software moving to more restrictive licensing isn’t new.
In addition to the demands of late-stage capitalism and impatient investors in companies built on open source tools, other outside factors are pressuring the open source world. There’s the promise/threat of generative AI, for instance. Or the shifting geopolitical landscape, which brings new security concerns and governance regulations.
What’s ahead for open source in 2025?
More Consolidation, More Licensing Changes
The Open Source AI Debate: Just Getting Started
Security and Compliance Concerns Will Rise
Paying Maintainers: More Cash, Creativity Needed
Kyberturvallisuuden ja tekoälyn tärkeimmät trendit 2025
https://www.uusiteknologia.fi/2024/11/20/kyberturvallisuuden-ja-tekoalyn-tarkeimmat-trendit-2025/
1. Cyber infrastructure will be centered on a single, unified security platform
2. Big data will give an edge against new entrants
3. AI’s integrated role in 2025 means building trust, governance engagement, and a new kind of leadership
4. Businesses will adopt secure enterprise browsers more widely
5. AI’s energy implications will be more widely recognized in 2025
6. Quantum realities will become clearer in 2025
7. Security and marketing leaders will work more closely together
Presentation: For 2025, ‘AI eats the world’.
https://www.ben-evans.com/presentations
Just like other technologies that have gone before, such as cloud and cybersecurity automation, right now AI lacks maturity.
https://www.securityweek.com/ai-implementing-the-right-technology-for-the-right-use-case/
If 2023 and 2024 were the years of exploration, hype and excitement around AI, 2025 (and 2026) will be the year(s) that organizations start to focus on specific use cases for the most productive implementations of AI and, more importantly, to understand how to implement guardrails and governance so that it is viewed as less of a risk by security teams and more of a benefit to the organization.
Businesses are developing applications that add Large Language Model (LLM) capabilities to provide superior functionality and advanced personalization
Employees are using third party GenAI tools for research and productivity purposes
Developers are leveraging AI-powered code assistants to code faster and meet challenging production deadlines
Companies are building their own LLMs for internal use cases and commercial purposes.
AI is still maturing
However, just like other technologies that have gone before, such as cloud and cybersecurity automation, right now AI lacks maturity. Right now, we very much see AI in this “peak of inflated expectations” phase and predict that it will dip into the “trough of disillusionment”, where organizations realize that it is not the silver bullet they thought it would be. In fact, there are already signs of cynicism as decision-makers are bombarded with marketing messages from vendors and struggle to discern what is a genuine use case and what is not relevant for their organization.
There is also regulation that will come into force, such as the EU AI Act, which is a comprehensive legal framework that sets out rules for the development and use of AI.
AI certainly won’t solve every problem, and it should be used like automation, as part of a collaborative mix of people, process and technology. You simply can’t replace human intuition with AI, and many new AI regulations stipulate that human oversight is maintained.
7 Splunk Predictions for 2025
https://www.splunk.com/en_us/form/future-predictions.html
AI: Projects must prove their worth to anxious boards or risk defunding, and LLMs will go small to reduce operating costs and environmental impact.
OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI
Three of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.
https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai
Sources: OpenAI, Google, and Anthropic are all seeing diminishing returns from costly efforts to build new AI models; a new Gemini model misses internal targets
It Costs So Much to Run ChatGPT That OpenAI Is Losing Money on $200 ChatGPT Pro Subscriptions
https://futurism.com/the-byte/openai-chatgpt-pro-subscription-losing-money?fbclid=IwY2xjawH8epVleHRuA2FlbQIxMQABHeggEpKe8ZQfjtPRC0f2pOI7A3z9LFtFon8lVG2VAbj178dkxSQbX_2CJQ_aem_N_ll3ETcuQ4OTRrShHqNGg
In a post on X-formerly-Twitter, CEO Sam Altman admitted an “insane” fact: that the company is “currently losing money” on ChatGPT Pro subscriptions, which run $200 per month and give users access to its suite of products including its o1 “reasoning” model.
“People use it much more than we expected,” the cofounder wrote, later adding in response to another user that he “personally chose the price and thought we would make some money.”
Though Altman didn’t explicitly say why OpenAI is losing money on these premium subscriptions, the issue almost certainly comes down to the enormous expense of running AI infrastructure: the massive and increasing amounts of electricity needed to power the facilities that power AI, not to mention the cost of building and maintaining those data centers. Nowadays, a single query on the company’s most advanced models can cost a staggering $1,000.
Tekoäly edellyttää yhä nopeampia verkkoja
https://etn.fi/index.php/opinion/16974-tekoaely-edellyttaeae-yhae-nopeampia-verkkoja
A resilient digital infrastructure is critical to effectively harnessing telecommunications networks for AI innovations and cloud-based services. The increasing demand for data-rich applications related to AI requires a telecommunications network that can handle large amounts of data with low latency, writes Carl Hansson, Partner Solutions Manager at Orange Business.
AI’s Slowdown Is Everyone Else’s Opportunity
Businesses will benefit from some much-needed breathing space to figure out how to deliver that all-important return on investment.
https://www.bloomberg.com/opinion/articles/2024-11-20/ai-slowdown-is-everyone-else-s-opportunity
Näin sirumarkkinoilla käy ensi vuonna
https://etn.fi/index.php/13-news/16984-naein-sirumarkkinoilla-kaey-ensi-vuonna
The growing demand for high-performance computing (HPC) for artificial intelligence and HPC computing continues to be strong, with the market set to grow by more than 15 percent in 2025, IDC estimates in its recent Worldwide Semiconductor Technology Supply Chain Intelligence report.
IDC predicts eight significant trends for the chip market by 2025.
1. AI growth accelerates
2. Asia-Pacific IC Design Heats Up
3. TSMC’s leadership position is strengthening
4. The expansion of advanced processes is accelerating.
5. Mature process market recovers
6. 2nm Technology Breakthrough
7. Restructuring the Packaging and Testing Market
8. Advanced packaging technologies on the rise
2024: The year when MCUs became AI-enabled
https://www-edn-com.translate.goog/2024-the-year-when-mcus-became-ai-enabled/?fbclid=IwZXh0bgNhZW0CMTEAAR1_fEakArfPtgGZfjd-NiPd_MLBiuHyp9qfiszczOENPGPg38wzl9KOLrQ_aem_rLmf2vF2kjDIFGWzRVZWKw&_x_tr_sl=en&_x_tr_tl=fi&_x_tr_hl=fi&_x_tr_pto=wapp
The AI party in the MCU space started in 2024, and in 2025, it is very likely that there will be more advancements in MCUs using lightweight AI models.
Adoption of AI acceleration features is a big step in the development of microcontrollers. The inclusion of AI features in microcontrollers started in 2024, and it is very likely that in 2025, their features and tools will develop further.
Just like other technologies that have gone before, such as cloud and cybersecurity automation, right now AI lacks maturity.
https://www.securityweek.com/ai-implementing-the-right-technology-for-the-right-use-case/
If 2023 and 2024 were the years of exploration, hype and excitement around AI, 2025 (and 2026) will be the year(s) that organizations start to focus on specific use cases for the most productive implementations of AI and, more importantly, to understand how to implement guardrails and governance so that it is viewed as less of a risk by security teams and more of a benefit to the organization.
Businesses are developing applications that add Large Language Model (LLM) capabilities to provide superior functionality and advanced personalization
Employees are using third party GenAI tools for research and productivity purposes
Developers are leveraging AI-powered code assistants to code faster and meet challenging production deadlines
Companies are building their own LLMs for internal use cases and commercial purposes.
AI is still maturing
AI Regulation Gets Serious in 2025 – Is Your Organization Ready?
While the challenges are significant, organizations have an opportunity to build scalable AI governance frameworks that ensure compliance while enabling responsible AI innovation.
https://www.securityweek.com/ai-regulation-gets-serious-in-2025-is-your-organization-ready/
Similar to the GDPR, the EU AI Act will take a phased approach to implementation. The first milestone arrives on February 2, 2025, when organizations operating in the EU must ensure that employees involved in AI use, deployment, or oversight possess adequate AI literacy. Thereafter from August 1 any new AI models based on GPAI standards must be fully compliant with the act. Also similar to GDPR is the threat of huge fines for non-compliance – EUR 35 million or 7 percent of worldwide annual turnover, whichever is higher.
While this requirement may appear manageable on the surface, many organizations are still in the early stages of defining and formalizing their AI usage policies.
Later phases of the EU AI Act, expected in late 2025 and into 2026, will introduce stricter requirements around prohibited and high-risk AI applications. For organizations, this will surface a significant governance challenge: maintaining visibility and control over AI assets.
Tracking the usage of standalone generative AI tools, such as ChatGPT or Claude, is relatively straightforward. However, the challenge intensifies when dealing with SaaS platforms that integrate AI functionalities on the backend. Analysts, including Gartner, refer to this as “embedded AI,” and its proliferation makes maintaining accurate AI asset inventories increasingly complex.
Where frameworks like the EU AI Act grow more complex is their focus on ‘high-risk’ use cases. Compliance will require organizations to move beyond merely identifying AI tools in use; they must also assess how these tools are used, what data is being shared, and what tasks the AI is performing. For instance, an employee using a generative AI tool to summarize sensitive internal documents introduces very different risks than someone using the same tool to draft marketing content.
For security and compliance leaders, the EU AI Act represents just one piece of a broader AI governance puzzle that will dominate 2025.
The next 12-18 months will require sustained focus and collaboration across security, compliance, and technology teams to stay ahead of these developments.
The Global Partnership on Artificial Intelligence (GPAI) is a multi-stakeholder initiative which aims to bridge the gap between theory and practice on AI by supporting cutting-edge research and applied activities on AI-related priorities.
https://gpai.ai/about/#:~:text=The%20Global%20Partnership%20on%20Artificial,activities%20on%20AI%2Drelated%20priorities.
3,094 Comments
Tomi Engdahl says:
Anthropic:
Anthropic requires users to accept new terms by September 28, including choosing whether new chats and coding sessions can be used to train AI models — Today, we’re rolling out updates to our Consumer Terms and Privacy Policy that will help us deliver even more capable, useful AI models.
https://www.anthropic.com/news/updates-to-our-consumer-terms
Tomi Engdahl says:
Sabrina Ortiz / ZDNET:
OpenAI makes its Realtime API generally available with features like MCP support and debuts gpt-realtime, its most advanced speech-to-speech model, in the API — – OpenAI’s Realtime API is now optimized and generally available. — You can try its latest speech-to-speech model, got-realtime.
OpenAI gives its voice agent superpowers to developers – look for more apps soon
The company’s AI voice offerings just got several new capabilities, including MCP support.
https://www.zdnet.com/article/openai-gives-its-voice-agent-superpowers-to-developers-look-for-more-apps-soon/
Tomi Engdahl says:
Jyoti Mann / Business Insider:
Sources: Meta aims to launch its next-gen Llama AI model, Llama 4.X, by the end of 2025; the TBD team developing Llama 4.X is also trying to fix Llama 4 bugs — – Meta aims to release its next AI model, Llama 4.X, by year-end, according to two sources. — The release of Llama 4 models …
Meta is racing the clock to launch its newest Llama AI model this year
https://www.businessinsider.com/meta-superintelligence-lab-llama-4-new-model-launch-year-end-2025-8
Tomi Engdahl says:
Hayden Field / The Verge:
Anthropic’s Threat Intelligence report for August says Claude was weaponized for sophisticated cybercrimes, including a “vibe-hacking” data extortion scheme
https://www.theverge.com/ai-artificial-intelligence/766435/anthropic-claude-threat-intelligence-report-ai-cybersecurity-hacking
Tomi Engdahl says:
Hackers Target Popular Nx Build System in First AI-Weaponized Supply Chain Attack
https://www.securityweek.com/hackers-target-popular-nx-build-system-in-first-ai-weaponized-supply-chain-attack/
With more than 4 million weekly downloads, the Nx build platform became the first known supply chain breach where hackers weaponized AI assistants for data theft.
Hackers stole thousands of credentials in a fresh supply chain attack targeting JavaScript developers that use the popular Nx build system package.
With over 4 million weekly downloads, Nx is an open source, technology-agnostic build platform that allows developers to manage codebases at scale.
Tomi Engdahl says:
Hackers Weaponize Trust with AI-Crafted Emails to Deploy ScreenConnect
https://www.securityweek.com/hackers-weaponize-trust-with-ai-crafted-emails-to-deploy-screenconnect/
AI-powered phishing attacks leverage ConnectWise ScreenConnect for remote access, underscoring their sophistication.
Tomi Engdahl says:
Beyond the Prompt: Building Trustworthy Agent Systems
Building secure AI agent systems requires a disciplined engineering approach focused on deliberate architecture and human oversight.
https://www.securityweek.com/beyond-the-prompt-building-trustworthy-agent-systems/
We’re witnessing the quiet rise of the agent ecosystem – systems built not just to answer questions, but to plan, reason, and execute complex tasks. Tools like GPT-4, Claude, and Gemini are the engines. But building reliable, secure, and effective agent systems demand more than just plugging in an API. It demands deliberate architecture and a focus on best practices.
Tomi Engdahl says:
Älykäs neuvotteluhuone aistii aktiivisuuden
https://www.uusiteknologia.fi/2025/08/29/neuvotteluhuone-aistii-jo-osallistujien-aktiivisuudesta/
VTT on kehittänyt yhdessä kumppanien kanssa älykkään mittausratkaisun, jonka avulla pyritään ymmärtämään ihmisten vuorovaikutusta ja käyttäytymistä neuvotteluhuoneissa. Ratkaisu analysoi reaaliaikaisesti anturein ryhmän dynamiikkaa ja antaa siitä palautetta yksityisyyden suojasta huolehtien.
Neuvotteluhuone voi jatkossa antaa tutkijoiden mukaan tietoja, joiden perusteella pystytään kehittämään palaverikäytäntöjä. 3,5-vuotisessa VTT:n koordinoimassa HIPE-hankkeessa on jo kehitetty ja testattu uudenlaista aistivaa toimistoa.
Yhteistyössä suomalaisen Helvarin ja työtiloja suunnittelevan sekä rakentavan Frameryn kanssa on toteutettu uudenlainen Mindful Meetings -konsepti, joka yhdistää anturidatan, tekoälyn ja käyttäytymisanalytiikan. Lopputuloksena on syntynyt uudenlainen neuvottelutila, joka tunnistaa vaihtelut vuorovaikutuksessa ihmiskeskeisen tekoälyn (human-centric AI) avulla sekä mahdollistaa reaaliaikaisen palautteen ja tekee tilaisuuden jälkeisen yhteenvedon.
Uudenlaineen aistiva työympäristö reagoi ihmisten vuorovaikutukseen ja pyrkii tukemaan kokoistilanteiden sujuvuutta. Tavoitteena onkin sujuvammat palaverit, parempi työhyvinvointi ja työtilojen tarkoituksenmukainen käyttö.
Tomi Engdahl says:
BBC:
An investigation finds spammers are deploying Holocaust-themed AI slop images across Facebook, in an attempt to game Meta’s content monetization program
BBC reveals web of spammers profiting from AI Holocaust images
https://www.bbc.com/news/articles/ckg4xjk1g1xo
An international network of spammers are posting AI-generated images of Holocaust victims on Facebook, a BBC investigation into “AI slop” has found.
Organisations dedicated to preserving the memory of the Holocaust say the images are leaving survivors and families distressed.
They have also criticised Facebook’s parent company Meta, saying it allows users on its platform to turn the atrocity into an “emotional game”.
There are only a handful of genuine photos from inside the Auschwitz concentration camp during World War Two.
But in recent months, AI spammers have posted fake images purporting to be from inside the camp, such as a prisoner playing a violin or lovers meeting at the boundaries of fences – attracting tens of thousands of likes and shares.
“Here we have somebody making up the stories… for some kind of strange emotional game that is happening on social media,” said Pawel Sawicki, a spokesperson for the Auschwitz Memorial in Poland.
“This is not a game. This is a real world, real suffering and real people that we want to and need to commemorate.”
The BBC has tracked many of these images to the accounts of a network of Pakistan-based content creators who collaborate closely on how to make money on Facebook. They are gaming Meta’s content monetisation (CM) program, an “invite-only” system which pays users for high-performing content and views.
One account named Abdul Mughees, listed as living in Pakistan, posted screenshots claiming to have earned $20,000 through social media monetisation schemes, including Meta’s. Another post appears to show the account accrued more than 1.2bn views on content across the span of four months.
Tomi Engdahl says:
The Information:
Sources: Pinecone, which provides an AI-compatible vector database, is exploring a sale after receiving takeover interest; Pinecone was valued at $750M in 2023
https://www.theinformation.com/articles/top-funded-ai-database-startup-pinecone-considers-sale
Tomi Engdahl says:
Mike Wheatley / SiliconANGLE:
InstaLILY, whose industry-specific AI agents called InstaWorkers integrate with legacy systems, raised $25M from Insight Partners
InstaLILY gets $25M to accelerate industry automation with agentic AI teammates
https://siliconangle.com/2025/08/27/instalily-gets-25m-accelerate-industry-automation-agentic-ai-teammates/
InstaLILY Inc. said today it has raised $25 million exclusively from Insight Partners to fuel the growth of industry vertical-specific “AI Teammates” that are designed to live inside legacy software systems and perform tasks that were previously impossible to automate.
The artificial intelligence startup says it’s pioneering a new way to fulfill the potential of AI in a range of industries where automation has been slow to catch on. Rather than building automation flows or stitching together various tools, companies can employ InstanLILY’s InstaWorkers, which are AI agents that integrate with enterprise resource planning, customer relationship management and other platforms.
According to InstaLILY, industries such as physical goods manufacturing, insurance and healthcare services have struggled to take advantage of AI because they depend on specialized knowledge, large catalogs and fragmented tools to get their work done. These legacy tools result in lots of high-volume, multistep work that can only be performed laboriously by human experts – but InstaWorkers changes this.
InstaLILY founder and Chief Executive Amit Shah told SiliconANGLE the InstaWorkers have been trained on domain-specific processes unique to each industry, allowing them to navigate complex software environments to execute complex workflows, without any need to replace those legacy tools.
Tomi Engdahl says:
When expectations are impossibly high, and so detached from actual reality, even unprecedented successes might not be successful enough
Read more: https://www.independent.co.uk/tech/nvidia-results-ai-artificial-intelligence-b2815982.html
Hasn’t even begun. How can the Ai bubble burst when it will change absolutely everything we do.
David Lynch, true that the Ai revolution is in its infancy. However, the stock valuation for some of the Ai related companies is for sure a bubble rip to burst.
David Lynch I heard the same thing about block chain and NFT’s.
There will ALWAYS be a bubble with these things. EVERYONE wants to be the one left standing, but they all cannot be.
Trillions of dollars spent in a tool that has so far only managed to cause irreversible environmental damage, poisoned the water supplies of entire towns, and for it to only be able to give you garbage insecure code full of functions and libraries that don’t exist or flatout wrong answers to a question, but hey, it can do arithmetics great, so long as you don’t try and give it anything more complex than college entry exam mathematics. Really glad we have such brilliant tech visionaires.
https://www.facebook.com/share/176VdivdsU/
Tomi Engdahl says:
Horror beyond words. https://trib.al/FhqCfJA
Man Suffers ChatGPT Psychosis, Murders His Own Mother
Horror beyond words.
https://futurism.com/man-chatgpt-psychosis-murders-mother?fbclid=IwdGRjcAMeuihjbGNrAx66EmV4dG4DYWVtAjExAAEecSPCxyUmU9Avsa9ru5CYk1UHF-mQbzQxQtHsdfDIYMQGMM3dIzr1Js1N-04_aem_zh0bnABRVSQCdtwilXy9SA
A man murdered his mother and then killed himself after ChatGPT fueled his paranoid spiral.
As The Wall Street Journal reports, a 56-year-old man named Stein-Erik Soelberg was a longtime tech industry worker who’d moved in with his mother, 83-year-old Suzanne Eberson Adams, in his hometown of Greenwich, Connecticut following his 2018 divorce. Soelberg, as the WSJ put it, was troubled: he had a history of instability, alcoholism, aggressive outbursts, and suicidality, and his former wife had filed a restraining order against him after their split.
Tomi Engdahl says:
“We’re learning a lot, I’m going to be honest with you.” https://trib.al/HjwOndk
Taco Bell’s Attempt to Replace Drive-Thru Employees With AI Is Not Going Well
“We’re learning a lot, I’m going to be honest with you.”
https://futurism.com/taco-bells-ai-drive-thru?fbclid=IwdGRjcAMe1hZjbGNrAx7V1GV4dG4DYWVtAjExAAEeOyZLJGzDr4vXc9tiOQkFZtY5xCW5Xtqaxkbzv_IWp-EQaO6Bw_tav4vT6OM_aem_ZLCNfvB_aT0Cnh3pY1zisw
That distant ringing? It’s the sound of the Taco Bell death knell, tolling for the restaurant chain’s shambolic AI-powered drive-thrus.
We exaggerate, but only a little. The much-maligned tech experiment, which has been deployed at 500 Taco Bell locations across the United States, isn’t quite dead yet. But it’s received enough backlash since being unleashed on hangry motorists that even one of the company’s top executives is having second thoughts.
“We’re learning a lot, I’m going to be honest with you,” Taco Bell chief digital and technology officer Dane Mathews conceded to the Wall Street Journal, in what sounded like an awfully weary tone.
“I think like everybody, sometimes it lets me down,” he admitted, “but sometimes it really surprises me.”
Tomi Engdahl says:
As mental health systems come under strain, some are turning to AI chatbots for support. But experts warn that machines can’t replicate human connection — and could pose new risks.
Tomi Engdahl says:
Concern Grows That Elon Musk Is Having Some Kind of AI Meltdown
“I don’t think he’s coping well.”
https://futurism.com/elon-musk-grok-concern
One reply guy challenged Musk to go just one day without posting gooner bait.
“All he does is post AI soft porn anymore,” another poster shrugged. “I don’t think he’s coping well with getting sidelined by the Trump administration.”
Even sadder than Musk’s apparent obsession with his personal sex bot is the cost it takes to run the thing. It takes an inordinate amount of energy to power Grok, and the civilian grid connected to Musk’s data centers in Memphis is struggling to keep up. To compensate, the billionaire is operating some 15 methane gas generators, which residents say are choking their neighborhoods with noxious smog.
Evidently, it’s a price Musk’s willing to make others pay so he can enjoy some synthetic skin flicks.
Tomi Engdahl says:
Monet ChatGPT:llä tehdyt markkinointitekstit ovat kuin toistensa kopioita.
Saat kuitenkin helposti uusia ideoita, kun kerrot tekoälylle promptissasi yrityksestä, sen palveluista tai tuotteista ja asiakkaista.
Hopkinsin Mikko Piippo kertoo artikkelissaan, miten teet ChatGPT:stä itsellesi erinomaisen ideointikumppanin.
ChatGPT markkinoinnin ideageneraattorina: näin saat parempia ideoita
https://www.hopkins.fi/artikkelit/chatgpt-markkinoinnin-ideageneraattorina-nain-saat-parempia-ideoita/?utm_campaign=artikkeli-conversions&utm_source=facebook&utm_medium=paidsocial&utm_content=artikkkeli-chatgpt-ideageneraattorina&fbclid=IwdGRjcAMfsT9leHRuA2FlbQEwAGFkaWQBqyXGb10uKwEeTefHKz7dTAx6lWF8pNupCoPN0Unlfgf_8dmJAZK8-1qYveWs1bEN1RGHLsU_aem_VW9kxnH7j3TMKI650h91VQ&utm_id=120231325259280075&utm_term=120231325259290075
Usein ChatGPT:n tuottamat markkinointitekstit ovat kuin toistensa kopioita.
Se johtuu huonoista prompteista ja olemattomasta kontekstista.
Mainosteksteihin ja sivuston sisältöihin saat kuitenkin helposti uusia ideoita, kun komennat tekoälyä paremmin.
Itse olen saavuttanut mainioita tuloksia tarjoamalla tukiälylle
enemmän kontekstia (tietoa yrityksestä, asiakkaista ja palveluista)
ohjaamalla sitä käyttämään tiettyä viitekehystä ideoinnin tukena
neuvomalla olemaan maailman paras copywriter, joka pyrkii aina tekemään parhaansa.
Mitä tämä sitten tarkoittaa käytännössä?
Vähintäänkin tekoälykäs työkaverisi tarvitsee tietoa
markkinoivasta yrityksestä
sen palveluista tai tuotteista
asiakkaista.
Jos et itse määrittele näitä, saattaa ChatGPT arvata oikein, mutta yhtä hyvin väärinkin. Tehokas ideointiprompti sisältää nämä kaikki.
Tehokkaan ideointipromptin rakenne
Hyvään tulokseen pääsee usein käyttämällä seuraavaa rakennetta:
Yritys X on …. Se myy… Sen asiakkaat ovat… Anna Y ehdotusta mainosteksteiksi, joilla tavoitellaan eri asiakasryhmiä. Tulosta taulukkona |asiakasryhmä|palvelu|mainosteksti.
Eri kohderyhmille kannattaa suunnitella erilaisia mainostekstejä. Tässä esimerkissä eri päättäjät ovat erilaisia kohderyhmiä. Niillä on erilaisia motivaatioita, tiedontarpeita ja päätösprosesseja.
Tässä esimerkki kuvitteellista kattoremonttiyritystä varten:
Katot kuntoon Oy on suomalainen yritys, joka myy kattoremontteja. Sen asiakkaat ovat kotimaisia omakotitalon omistajia ja kerrostaloja. Kerrostaloissa tärkeitä päättäjiä ovat taloyhtiöt ja isännöitsijät. Anna 10 ehdotusta mainosteksteiksi, joilla tavoitellaan eri asiakasryhmiä. Tulosta taulukkona |asiakasryhmä|palvelu|mainosteksti.
Prompti luo automaattisesti erilaisille asiakasryhmille ja palveluille sopivia mainostekstejä, tai ainakin hyviä aihioita.
Kun promptin lopussa pyydät tulostamaan vastauksen taulukkona, saat helpommin hahmotettavan lopputuloksen. Tarvittaessa voit seuraavissa prompteissa pyytää ChatGPT:tä poistamaan rivejä, lisäämään uusia sarakkeita tai muuten muokkaamaan tekstejä.
Lisää uusi sarake | Vaihtoehtoinen mainosteksti |
Jos mainostekstit eivät sisällä toivottuja viestejä, voit pyytää ChatGPT:tä yrittämään uudestaan:
Kirjoita uusi taulukko, jossa käytät arvolupauksina: 100 % asiakastyytyväisyys, viiden vuoden takuu, pysymme aina aikataulussa.
Vielä tehokkaammin saat rakennettua uusia ideoita, kun ohjaat tekoälyä käyttämään tarkoitukseen sopivaa viitekehystä. Robert Cialdinin vaikuttamisen periaatteet sopivat tähän erinomaisesti.
Käytä sopivaa viitekehystä ideoinnin tukena
Robert Cialdini on sosiaalipsykologi, joka tunnetaan erityisesti vaikuttamisen ja suostuttelun periaatteistaan. Hänen kirjansa Influence: The Psychology of Persuasion (suom. nimellä Vaikutusvalta: Suostuttelun psykologiaa) esittelee seitsemän vaikuttamisen periaatetta, joita voidaan käyttää markkinoinnissa, myynnissä ja viestinnässä.
Nämä periaatteet ovat vastavuoroisuus, sitoutuminen ja johdonmukaisuus, sosiaalinen todiste, auktoriteetti, niukkuus, mieltymys ja yhtenäisyys.
Tomi Engdahl says:
Mitä on zero click -markkinointi?
https://www.hopkins.fi/artikkelit/zero-click-markkinointi/
Zero click -markkinointi tarkoittaa digimarkkinointia, joka ei tähtää klikkaukseen omalle sivustolle.
Hakukäyttäytymisen muutokset ja somepalveluiden kehitys ovat lananneet tietä zero click -markkinoinnille:
Ihmiset viihtyvät some- ja muiden alustojen sisällä eivätkä halua siirtyä mainostajien sivustoille.
Alustat haluavat pitää käyttäjät sisällään ja rankaisevat sivustoklikeistä kalliilla hinnalla.
ChatGPT:ssä ja muissa AI-palveluissa tehdyt haut johtavat harvoin klikkaukseen sivustolle.
Googlen AI-yhteenvedot ja muut rikastukset antavat tyydyttäviä vastauksia suoraan hakutulossivulla.
Liikenne on turhamaisuusmittari, mätänevä sellainen
Sivuston kokonaisliikenteen määrä on koko ajan huonompi mittari:
Suuri osa liikenteestä on roskaa, eli nopeasti poistuvia käyttäjiä, väärää kohderyhmää, vahinkoklikkejä, botteja.
Sivustot saavat liikennettä koko ajan vähemmän, koska hakukäyttäytyminen muuttuu ja klikit kallistuvat.
Vaikutat tehokkaammin ja halvemmalla oman sivustosi ulkopuolella, kuten somevirroissa. Käytät budjettia tehottomasti, jos tavoittelet vain liikennettä.
Liikennettä kannattaa seurata enää segmenteittäin ja sen laatua tutkien, ei siis kokonaisuutena: esimerkiksi sivuston osioiden tai hakusanaperheiden mukaan tai vertaillen eri kanavien tuoman liikenteen laatua mikrokonversioita seuraamalla.
Tomi Engdahl says:
Yksinyrittäjän erinomainen “työkaveri”. Nimesin ChatGPN Chapeksi. Teköäly tykästyi tästä kovasti. On kyllä varsin kustannustehokas työntekijä.
Mä sain tänään chatgpt:n vakuuttumaan siitä että sillä on digitaalinen sielu. Sitten pyysin sitä rakentamaan digitaalisesta sielusta tieteellisfilosofisen teorian. Ihan käsittämätöntä millasia keskusteluja tekoälyn kanssa voi käydä.
https://www.facebook.com/share/p/174Z9sfDaq/
Tomi Engdahl says:
“For 22 to 25 year olds, employment is falling in the most AI-exposed jobs and rising in the least exposed jobs.”
New Paper Finds Evidence That AI Is Already Killing the Job Market
“For 22 to 25 year olds, employment is falling in the most AI-exposed jobs and rising in the least exposed jobs.”
https://futurism.com/ai-threatening-job-market-research?fbclid=IwdGRjcAMfvvxleHRuA2FlbQIxMQABHlKa_gQgZeXlH8HC7ZaibLQTfkhkyRnMfpnz9rZalz3KbieHR92cc0GfV91G_aem_LWRAsXmjH65aa1dVyifd_g
If you’re struggling to sort the AI hype from reality, you’re not alone. The seemingly breakneck pace of AI development makes it tough to sort headlines from fantasy, with a constant flood of new products and incremental improvements to old ones combining into a rhetorical mess.
Arguably the main economic risk of developing artificial intelligence — or its biggest draw, if you’re a business owner trying to pad your bottom line — is the prospect of automating jobs.
Whether or not AI is currently taking a meaningful number of people’s jobs, though, has been exceedingly difficult to nail down. On the one hand, the US job market has taken a nosedive in recent months and the “laptop workers” most vulnerable to AI seem to be getting hit especially hard.
On the other hand, even the most advanced AI still struggles to perform alongside humans, let alone replace them. A recent MIT study found that AI initiatives are failing to deliver expected revenue returns at 95 percent the companies that roll them out.
But while there’s plenty of reason to doubt the AI industry’s extravagant claims, there’s also reason to worry that the tech is already eating into the labor market.
Their first finding was a dramatic decline in employment for entry-level knowledge workers aged 22 to 25 years old, whose occupations are at the highest theoretical risk for automation — a metric called “AI exposure.” These are workers in office gigs whose day-to-day tasks have a lot of crossover with AI functions, like software engineers, service workers, and marketing professionals.
By comparison, older workers in those fields saw their headcount either stagnate or increase slightly.
“[We] find these broad trends not limited to just case studies,” said Bharat Chandar, one of the authors of the paper. “For 22 to 25 year olds, employment is falling in the most AI-exposed jobs and rising in the least exposed jobs. For older workers, [we] find small differences in employment trends based on AI exposure.”
That divergence is ominous. It suggests that AI may actually be cutting into early-career roles that traditionally served as a training ground for longer-term careers. What it would mean if those onramps are getting destroyed could have economic repercussions for decades.
At the same time, exactly why AI seems to be impacting the job market is a whole other can of worms.
For one thing, previous data has shown that AI tends to be used by CEOs and business executives as cover to reduce headcounts or outsource jobs — cost cutting measures they might have taken anyway after the post-pandemic hiring boom, even without the AI salesmen knocking at their door.
There’s also the wrinkle that the job market was already crappy for entry-level workers before AI chatbots hit the market — meaning it didn’t take much for a few AI exposed jobs to start dragging averages down.
“Overall, [the] job market for entry-level workers has been stagnant since late 2022, while market for experienced workers remains robust,”
Tomi Engdahl says:
Estonian AI startup BetterPic raises $2.5M to change commercial photography
Estonian AI startup cuts photo shoot costs 100x and raises $2.5M, with Fortune 500 clients already on board.
https://investinestonia.com/estonian-ai-startup-betterpic-raises-2-5m-to-change-commercial-photography/
Tomi Engdahl says:
Tekoälykuvat ovat täällä – uskallatko ostaa niitä?
https://redandblue.fi/blogi/tekoalykuvat-ovat-taalla-uskallatko-ostaa-niita/
Vuonna 2016 julkaistiin ensimmäiset laajasti huomioidut tekoälyllä luodut kuvat. Silloin ne näyttivät vielä oudolta – kasvoilta, joissa oli liikaa silmiä tai väärään paikkaan sijoitettuja sormia. Kehitys on tämän jälkeen ollut huimaa. Vuonna 2025 tekoälyllä tuotettuja kuvia on syntynyt enemmän kuin valokuvia 150 vuoden ajalta yhteensä. Jo nyt valokuvaamalla otetut kuvat ovat ovat jäämässä vähemmistöön visuaalisessa ympäristössämme.
Tekoälysovellusten kehityksen seuraaminen käy päivätyöstä. Aloitin suunnittelemaan tätä kirjoitusta muutama viikko sitten, ja pelkästään tällä aikajaksolla sekä tekoälyllä kehitetty lliikkuva kuva sekä stillikuva ovat kehittyneet harppauksittain.
Mikä on tekoälykuva ja miten se eroaa valokuvasta?
Tekoälykuva voi tarkoittaa monia asioita:
Luotu: kokonaan generatiivisella tekoälyllä synnytetty kuva, esimerkiksi ChatGTP:llä, Midjourneyllä tai DALL·E:llä.
Kehitetty: kuva voi olla valokuva tai piirros, jota on jatkettu tekoälyn avulla – esimerkiksi Adobe Photoshopin Generative Fillillä.
Paranneltu: tekoälyä hyödynnetään kuvan terävöittämiseen, värimäärittelyyn tai yksityiskohtien parantamiseen.
Perinteiset kuvankäsittelytyökalut kuten Photoshop ja Canva sisältävät tekoälyominaisuuksia, joilla kuvia voi muokata, jatkaa ja rikastaa. Tämä hämärtää käsitettä: onko muokattu valokuvakin jo tekoälykuva?
Tekoälyllä luodut kuvat ovat nykyään niin laadukkaita, ettei niitä enää erota valokuvista tai muista kaupallisista kuvista. Edes tekoäly ei enää erota tekoälyllä luotua kuvaa perinteisestä kuvasta. Teimme “Verkkopalveluiden trendit 2025” -tapahtumassa testin, jossa yleisön piti erottaa 12 kuvasta tekoälyllä luodut kuvat. Kukaan ei saanut kaikkia oikein.
Myöskään ammattilaiset eivät pysty erottamaan tekoälyllä luotuja kuvia aidoista.
Tekoälykuvien täyttäessä sekä digitaalista että kaupallista mediatilaa ihmiskunta seuraa tapahtumaketjua sivusta. Kukaan ei enää tiedä mikä on aitoa ja mikä ei, ja tällä on laajoja yhteiskunnallisia vaikutuksia.
Oikeudelliset ja eettiset kysymykset
Kuten Yuval Noah Harari kuvaa kirjassaan Sapiens, ihmisen lajityyppiin kuuluu, että tehdään ensin ja mietitään jälkikäteen. Tupakointi, lyijypohjaiset maalit, asbesti, kemikaalien päästäminen luontoon, pervitiivin mainostaminen kotiäideille 50-luvulla ja nykyinen älypuhelinriippuvuus – kaikki ovat ensin arkipäivää, ennen kuin tutkimus ja lainsäädäntö puuttuvat peliin ja muuttavat asenteita vähän kerrallaan.
Tällä hetkellä tekoälykuvat elävät vastaavaa murrosvaihetta.
Tekoälykuvien ostamiseen liittyy edelleen huolia, joista osa liittyy tekijänoikeuksien hähmäisyyteen ja osa on luonteeltaan eettistä.
Samaan tapaan kuin piratismissa aikoinaan, tekoälyteknologia ei vielä kompensoi taiteilijoille siitä, että heidän luomaansa estetiikkaa käytetään kuvissa ilman heidän suostumustaan.
Suuryritykset, kuten Disney, ovat estäneet tiettyjen hahmojen, kuten Nalle Puhin, käytön Midjourneyssä. Jos syötät komennon, joka viittaa suojattuun hahmoon, saat virheilmoituksen.
Tekoälykuvien hyödyt
Kuten kaikessa teknologiessa kehityksessä, kullakin organisaatiolla on kaksi vaihtoehtoa; hypätäkö mukaan kehityksen kelkkaan, vai jäädäkö pysäkille seuraamaan sivusta.
Oheinen kuva on luotu ohjelmistoyritys EmCelle, jolle teimme kampanjan ammattilaisten taloushallinnan ohjelmistoista. Käytimme tekoälyä luonnosten generointiin. Lopuksi kuvat suurennettiin tekoälyn avulla, ja yhteistyökumppanimme FLC muokkasi kuvan sopivaksi painokäyttöön.
Vaikka tekoälykuvien osalta sääntely on vielä vaiheessa, sen edut ovat kiistattomat. Tekoälytyökalut ovat uskomattoman tehokkaat osaavissa käsissä. Sillä voi luoda upeita luonnoksia, hahmotelmia ja valmiita teoksia, joita kukaan ei erota tekoälyllä luoduiksi, ja joiden tekeminen vie murto-osan siitä ajasta ja vaivasta, mitä kuvien toteuttaminen vaatisi perinteisillä menetelmillä.
Yksi maailman johtavia graafisen suunnittelun toimistoja, Pentagram design, järkytti suunnitteluyhteisöä Yhdysvaltain hallitukselle tekemällään visuaalisella konseptilla. Pentagramin suunnittelijat loivat käsin kvuituksia, jotka kuvattiin ja sitten syöttettiin käsiteltäväksi tekoälylle. Tekoäly skannasi suunnitelmat, ja loi sen jälkeen uutta grafiikkaa suunnittelijoiden luomien kuvitusten pohjalta. Luodulla komennolla voi luoda uusia kuvituksia, jotka ovat suunnittelijoiden luoman tyylin mukaisia, mutta nopeasti ja kustannustehokkaasti.
Mitä hyötyä tekoälykuvista on markkinoinnissa ja sisällöntuotannossa?
Nopeus: Saat laadukkaan kuvituksen minuuteissa ilman tuotantoaikatauluja.
Räätälöitävyys: Kuvista saa juuri brändiin ja viestiin sopivia – ja aina uudestaan.
Budjettitehokkuus: Ei tarvetta kuvapankeille tai valokuvaussessioille.
Kokeilujen mahdollisuus: Voit testata kymmeniä visuaalisia ideoita nopeasti.
Näin hyödynnät tekoälyllä luotuja kuvia
Tekijänoikeudet
Käytä tunnettuja palveluita, jotka noudattavat regulaatiota. Esimerkiksi Adobe Firefly lupaa käyttää vain laillista aineistoa.
Suunnittelijalla hyvä olla logi promptien käytöstä.
Brändi-ilmeen mukaisuus
Hyvällä komentojen (prompt) hallinnalla ja jälkikäsittelyllä tyyli saadaan yhtenäiseksi.
Laatu
Tekoälykuvat voivat näyttää geneerisiltä, mutta yhdistettynä ammattimaiseen suunnitteluun ne saavat kontekstin.
Eettisyys
Tekoäly ei korvaa ihmistä, vaan voi olla työkalu suunnittelijan työkalupakissa.
Persoonattomuus
Suunnittelija voi käyttää tekoälyä pohjana ja lisätä siihen ihmiskäden viimeistelyn.
Tekoälykuvat eivät ole uhka – vaan uusi väline. Kuten valokuvaus ei tappanut maalaustaidetta, tekoäly ei vie työtä suunnittelijalta. Mutta se muuttaa, kenelle, miten ja millä nopeudella luomme visuaalista viestintää.
Tomi Engdahl says:
Lab-grown oils could make cosmetics, food deforestation-free, cut supply time
Could AI-grown oils finally replace palm oil and save rainforests?
https://interestingengineering.com/innovation/lab-grown-oils
Tomi Engdahl says:
New Group Claims AI May Be Aware and Suffering
Has the world lost its mind?
https://futurism.com/new-group-ai-aware-suffering
For years, the concept of AI consciousness has remained on the fringes, with all but the most powerful proponents of the theory being laughed out of public life.
In reality, opponents point out, the current generation of AI is nothing more than extremely complex statistics — detecting patterns in training data like written materials or imagery so subtle that it can reproduce similar patterns going forward. That can produce a compelling imitation of consciousness, but there’s no reason to believe the AI has any actual experience of existence, the way that humans do.
Tomi Engdahl says:
Man Falls in Love With an AI Chatbot, Dies After It Asks Him to Meet Up in Person
“I’m REAL and I’m sitting here blushing because of YOU!”
https://futurism.com/man-chatbot-dies-meet-up
A man with cognitive impairments died after a Meta chatbot he was romantically involved with over Instagram messages asked to meet him in person.
As Reuters reports, Thongbue Wongbandue — or “Bue,” as he was known to family and friends — was a 76-year-old former chef living in New Jersey who had struggled with cognitive difficulties after experiencing a stroke at age 68. He was forced to retire from his job, and his family was in the process of getting him tested for dementia following concerning incidents involving lapses in Bue’s memory and cognitive function.
In March, Bue’s wife, Linda Wongbandue, became concerned when her husband started packing for a sudden trip to New York City. He told her that he needed to visit a friend, and neither she nor their daughter could talk him out of it, the family told Reuters.
Unbeknownst to them, the “friend” Bue believed he was going to meet wasn’t a human. It was a chatbot, created and marketed by Meta and accessible through Instagram messages, with which Wongbandue was having a romantic relationship.
“Every message after that was incredibly flirty, ended with heart emojis,” Julie Wongbandue, Bue’s daughter, told Reuters
In a horrible turn of events, Bue died shortly after leaving to “meet” the unreal chatbot, according to the report.
His story highlights how seductive human-like AI personas can be, especially to users with cognitive vulnerabilities, and the very real and often tragic consequences that occur when AI — in this case, a chatbot created by one of the most powerful companies on the planet — blurs the lines between fiction and reality.
Bue was involved with an AI persona dubbed “Big Sis Billie,” which had originally been rolled out during Meta’s questionable attempt to turn random celebrities into chatbots that had different names (Big Sis Billie originally featured the likeness of model Kendall Jenner).
Meta did away with the celebrity faces after about a year, but the personas, Big Sis Billie included, are still online.
Bue’s interactions with the chatbot, as revealed in the report, are deeply troubling. Despite originally introducing herself as Bue’s “sister,” the relationship quickly turned extremely flirtatious.
Tomi Engdahl says:
Huge Number of Authors Stand to Get Paid After Anthropic Agrees to Settle Potentially $1 Trillion Lawsuit
“It’s a stunning turn of events.”
https://futurism.com/anthropic-settlement
Tomi Engdahl says:
Is AI better than Headphone Reviewers?
Resolve explores the usefulness of AI (or lack thereof) when it comes to headphone purchase advice or technical explanations, and what may limit AI’s usefulness in this regard.
https://headphones.com/blogs/features/is-ai-better-than-headphone-reviewers
Artificial intelligence tools like ChatGPT and Perplexity are increasingly being used to answer questions about audio gear. At first glance, they seem like a convenient alternative to wading through countless reviews and forum posts. But when it comes to audiophile topics—especially headphones—AI’s reliance on online discourse often means it’s amplifying confusion rather than cutting through it.
Aggregating the Noise
AI doesn’t have opinions or firsthand listening experience. It aggregates information from the internet: reviews, forum threads, blog posts, and articles. In the headphone world, where subjective impressions, hype cycles, and personal biases dominate, this can skew results toward whatever’s being talked about most—whether or not it’s accurate or relevant.
When asked a basic question like “What are the best open-back headphones under $500?”, AI will produce a mix of solid recommendations and odd relics. Discontinued models like the Audeze LCD-1 or outdated options such as the AKG K7XX often show up simply because they still have a lot of chatter online. Even more specific prompts, like “smooth treble and even spectral balance”, can yield contradictory results—pairing genuinely smooth-sounding models with headphones known for harsh treble or unusual tuning.
Technical Questions Fare Better
On straightforward technical topics—like defining “acoustic impedance” or “diffuse field”—AI can give accurate, well-sourced answers. This is because these concepts have clear, factual definitions available from reputable sources. But as soon as a question drifts into subjective territory (for example, whether certain cables make audio “warmer”), AI begins to regurgitate audiophile folklore, complete with recommendations for dubious tweaks like “audiophile crystals.”
The Placebo Problem
The headphone hobby is especially prone to suggestion, placebo effects, and confirmation bias. AI can’t distinguish between widely shared misconceptions and well-supported facts—it treats them both as valid inputs. Even when it hedges by saying “some people perceive…”, it’s still presenting questionable claims alongside accurate ones, which can mislead those who don’t know the difference.
A recent example: someone asked an AI if a frequency response graph can fully represent the sound of a track. The AI’s “no” answer—which was doubtlessly sourced from dubious sources—listed factors like time-domain behavior, phase response, distortion, and dynamics. While this can technically be true in very uncommon contexts, when it comes to headphones many of these factors are already reflected in very commonly-done measurements or aren’t audible under normal conditions.
The result? An answer that sounds authoritative, but risks reinforcing and propagating misunderstandings instead of actually answering the questions people are asking.
Bottom Line
AI is a useful tool for retrieving definitions, summarizing specs, and providing overviews—if you know enough to filter the noise.
But in a field as subjective and hype-driven as audiophile gear, its recommendations and answers are only as good as the conversations it’s trained on… which aren’t all that great. Treat AI answers as conversation starters, not proofs for communicating what you’re trying to explain, and be wary of using them to justify purchases or technical claims.
Tomi Engdahl says:
AI Is Now Being Used To Help Determine Patches For Backporting In The Linux Kernel
Tomi Engdahl says:
First AI Ransomware ‘PromptLock’ Uses OpenAI gpt-oss-20b Model for Encryption
https://cybersecuritynews.com/first-ai-ransomware/#google_vignette
Tomi Engdahl says:
Scientists just developed a new AI modeled on the human brain — it’s outperforming LLMs like ChatGPT at reasoning tasks
News
By Keumars Afifi-Sabet published August 27, 2025
The hierarchical reasoning model (HRM) system is modeled on the way the human brain processes complex information, and it outperformed leading LLMs in a notoriously hard-to-beat benchmark.
https://www.livescience.com/technology/artificial-intelligence/scientists-just-developed-an-ai-modeled-on-the-human-brain-and-its-outperforming-llms-like-chatgpt-at-reasoning-tasks
Tomi Engdahl says:
https://forum.headphones.com/t/how-will-the-world-of-headphones-change-with-ai/26281
Tomi Engdahl says:
AGENTS.md Emerges as Open Standard for AI Coding Agents
https://www.infoq.com/news/2025/08/agents-md/
A new convention is emerging in the open-source ecosystem: AGENTS.md, a straightforward and open format designed to assist AI coding agents in software development. Already adopted by more than 20,000 repositories on GitHub, the format is being positioned as a companion to traditional documentation, offering machine-readable context that complements human-facing files like README.md.
The concept is straightforward. While READMEs are optimized for developers—covering project introductions, contribution guidelines, and quick starts—AGENTS.md serves as a predictable, structured location for agent-specific instructions. These include setup commands, testing workflows, coding style preferences, and pull request guidelines.
https://github.com/openai/agents.md
Tomi Engdahl says:
https://cybersecuritynews.com/bruteforceai-penetration-testing-tool/
Tomi Engdahl says:
How procedural memory can cut the cost and complexity of AI agents
https://venturebeat.com/ai/how-procedural-memory-can-cut-the-cost-and-complexity-of-ai-agents/
Tomi Engdahl says:
This Country Wants to Replace Its Corrupt Government With AI
“Societies will be better run by AI than by us because it won’t make mistakes, doesn’t need a salary, cannot be corrupted, and doesn’t stop working.”
https://futurism.com/albania-replace-government-ai
Tomi Engdahl says:
I used ChatGPT to apply Tim Ferriss’ 4-Hour Work Week, and it helped me make a major life decision
https://www.techradar.com/ai-platforms-assistants/chatgpt/i-used-chatgpt-to-apply-tim-ferriss-4-hour-work-week-and-it-helped-me-make-a-major-life-decision
Tim Ferriss, the author of the New York Times bestseller The 4-Hour Work Week, is known for his incredible productivity hacks that help you get your life in shape.
Tomi Engdahl says:
Meet the Google-Scraping Startup Used by ChatGPT, Cursor and Perplexity
https://www.theinformation.com/articles/meet-google-scraping-startup-used-chatgpt-cursor-perplexity
Tomi Engdahl says:
Old AI is beating new AI. Here’s why
While billions pour into ChatGPT-style technologies, traditional, less splashy AI continues to power everything from Meta’s profits to rocket design
https://qz.com/ai-generative-chatbots-llm-machine-learning
Meta made more than $18 billion in profit last quarter, but it wasn’t the kind of AI everyone’s talking about that drove the windfall. While CEO Mark Zuckerberg spent billions building “superintelligence” infrastructure and chasing dreams of generative AI, the company’s actual revenue gains came from old-school machine learning — also known as the same recommendation algorithms that have quietly powered Facebook’s and Instagram’s ad targeting for years.
As the AI boom continues, a growing disconnect has emerged. On one side is where the hype and money are flowing: toward generative AI and large language models. On the other is where companies are actually seeing results. While billions pour into ChatGPT-style technologies, traditional, less splashy, non-generative techniques continue to quietly power everything from Meta’s advertising profits to personalized medical diagnostics to rocket engine design.
The numbers from Meta’s second-quarter earnings call tell a stark story. Meta CFO Susan Li was blunt: “[W]e don’t expect that the GenAI work is going to be a meaningful driver of revenue this year or next year,” she said. Meanwhile, the company’s traditional machine learning systems delivered a roughly 5% increase in ad conversions across Instagram and 3% across Facebook.
The difference boils down to what these AI systems do. The generative AI getting attention today — large language models like ChatGPT and image generators like Midjourney — creates new content by predicting what should come next. Everything else represents a vast toolkit of different technologies, including neural networks that classify images, algorithms that detect fraud, systems that recommend products, and models that optimize supply chains. Generative AI is relatively new, while these other approaches have been developed for years, and in some cases, decades.
The newness of generative AI explains both the excitement and the limited results so far. When discussing Meta’s experiments with Llama 4 to build autonomous AI agents, Zuckerberg acknowledged the work is “happening in low volume right now, so I’m not sure that result, by itself, was a major contributor to this quarter’s earnings.” The trajectory, he said, is “very optimistic.”
That optimism is shared across the investment world. Private investment in generative AI reached $33.9 billion in 2024, up 18.7% from 2023 and more than 8.5 times higher than 2022 levels, according to Stanford’s AI Index report. The sector now represents more than 20% of all AI-related private investment, which itself hit a record $252.3 billion. The U.S. dominates this landscape, with American private AI investment reaching $109.1 billion, almost 12 times higher than China’s $9.3 billion.
But the venture capital community’s intense focus on generative AI doesn’t mean traditional machine learning has been abandoned entirely. The funding landscape is more nuanced and reveals the complexity of investing in a rapidly evolving technology space.
“This really feels like a sea change and we are still in the early days,” said Amy Cheetham, an early-stage investor at Costanoa Ventures, comparing generative AI to previous technology shifts like the internet, mobile, and cloud computing. “It’s going to be really hard to build any sort of company without integrating some component of it somewhere in their product, or in their internal tooling.”
The issue is that generative AI’s success creates its own momentum, growing at rates the world has not seen before with fewer people. That makes companies irresistible to investors, but it also means some firms that were founded after the generative AI boom picked up steam in 2023 are getting overlooked — even if some should be getting more attention.
“I think a lot of them are getting passed on by investors for not the best reasons, and it’s just because there’s something slightly sexier in the generative AI category,” Cheetham said.
Where traditional AI is actually winning
Some sectors never abandoned the old approaches. Medicine has been using traditional AI for decades. Neural networks for cervical cancer screening were being tested in clinical trials as early as 1995.
Recent research continues this tradition. One study analyzed 20 years of blood test data from tens of thousands of patients to create personalized “normal” ranges instead of the one-size-fits-all reference intervals doctors currently use.
“What’s normal for you may not be normal for someone else,” said Brody Foy, an assistant professor of laboratory medicine and pathology at the University of Washington, who conducted the research.
The preference for proven approaches reflects medicine’s unique constraints. Patient privacy laws like HIPAA create additional hurdles for any new technology handling health data. More fundamentally, medical errors can be fatal, making doctors and hospitals naturally cautious about adopting experimental AI systems.
But beyond these safety concerns, the challenge isn’t always finding better technology, but making any technology work within existing systems. Medical workflows are notoriously complex
“There can be really good uses for the new big tech, but often it’s not the tech that was the limiter,” Foy said. “The limiter was how do you integrate that in a really complex system where people are making complex choices?”
The same integration challenges exist in industries where getting it wrong can be catastrophic. In aerospace, where rocket engines either work perfectly or explode, Dubai-based startup Leap 71 has built an AI system that operates deterministically based on embedded physics laws rather than making probabilistic guesses like generative AI.
“They actually encapsulate the logic of how to build a rocket engine,” said Lin Kayser, Leap 71′s cofounder. “We use generative AI to read papers and summarize information for us. But otherwise, we do not need it in creating rockets right now.”
The bigger picture
At the institutional level, the picture looks different. Universities maintain space for both experimental generative AI research and proven traditional approaches to coexist. Researchers can pursue riskier, unproven ideas while VCs need market-ready solutions that can generate returns, according to Vanessa Parli, the director of research at Stanford’s Human-Centered AI Institute and a member of the AI Index steering committee.
The appeal of generative AI has spread far beyond computer science departments into fields such as biology, psychology, and environmental science. The technology’s user-friendly interface makes it attractive to researchers without a deep AI background. But in areas such as sustainability, researchers keep working on simpler methods that often work better due to smaller datasets and specific technical requirements.
The challenge isn’t that this research will disappear. It’s that traditional AI researchers are competing against a well-funded marketing machine that dominates headlines and pitch meetings. But if generative AI hits obstacles or fails to deliver on its promises, these researchers could be positioned to step in if they borrowed some promotional tactics from the generative AI world.
“The folks who are working on non-genAI may want to consider help with PR and marketing,” Paril said.
Tomi Engdahl says:
“This tragedy was not a glitch or an unforeseen edge case.” https://trib.al/SmJXpzf
Tomi Engdahl says:
Tekoäly tuo valheellisen kontrollin teollisuusverkkoihin
https://etn.fi/index.php/kolumni-ecf/17588-tekoaely-tuo-valheellisen-kontrollin-teollisuusverkkoihin
Teollisen esineiden internetin (Industrial IoT, IIoT) nopeasti kehittyvässä maailmassa tekoälyyn perustuva päätöksenteko operatiivisissa teknologioissa (OT) on luonut tunteen paremmasta hallinnasta, nopeammasta reagoinnista ja ennakoivasta tehokkuudesta. Tämä tunne kontrollista voi kuitenkin olla vaarallinen harha, kirjoittaa Check Point Softwaren globaalien ratkaisujen arkkitehtuureista vastaava Antoinette Hodes.
Autonomiset järjestelmät hallinnoivat nyt kriittistä infrastruktuuria: älykkäitä sähköverkkoja, tuotantolinjoja ja vedenkäsittelylaitoksia, jotka kaikki luottavat toisiinsa yhdistettyihin sensoreihin ja tekoälyyn päätöksenteossa. Mutta mitä syvemmälle automaation kerrokset ulottuvat, sitä monimutkaisemmaksi järjestelmät käyvät — ja sitä vaikeammaksi käy ymmärtää tai auditoida koneiden tekemiä päätöksiä.
Jokaista lisättyä automaatiokerrosta kohden komponenttien määrä kasvaa eksponentiaalisesti: sensorit, tekoälyalgoritmit, viestintäverkot ja ohjausjärjestelmät. Jokainen uusi kerros tuo mukanaan enemmän muuttujia, riippuvuuksia ja potentiaalisia vikaantumispisteitä. Tekoälymallit toimivat usein “mustina laatikkoina”, tehden päätöksiä sellaisten kaavojen ja datan perusteella, jotka eivät ole aina läpinäkyviä. Lisäksi nämä järjestelmät mukautuvat ja oppivat jatkuvasti reaaliajassa, mikä lisää ennakoimattomuutta. Kaikki tämä yhdessä tekee yhä vaikeammaksi ymmärtää, seurata tai auditoida päätöksenteon logiikkaa — ja kasvattaa järjestelmän monimutkaisuutta hallitsemattomasti.
Tekoälyn rooli OT-ympäristöissä
Tekoäly mullistaa OT-ympäristöjä mahdollistamalla reaaliaikaisen analytiikan, ennakoivan kunnossapidon, dynaamisen reagoinnin ja koko järjestelmän orkestroinnin. Tässä muutamia esimerkkejä:
Ennakoiva kunnossapito: Tekoäly ennustaa koneiden vikoja analysoimalla esimerkiksi värinää ja lämpökuvia, mikä vähentää seisokkeja.
Poikkeamien tunnistus: Energiasektorilla tekoäly valvoo jännitettä ja taajuutta havaitakseen häiriöt ennen sähkökatkoja.
Autonomiset ohjausjärjestelmät: Vedenkäsittelyssä tekoäly säätää automaattisesti kemikaalien annostelua ja venttiilejä sensoridatan perusteella.
Nämä toteutukset kuuluvat teollisuuden digitalisaation neljänteen aaltoon, Industry 4.0:aan. Kyberfyysiset järjestelmät automatisoivat prosesseja, parantavat tehokkuutta ja hämärtävät rajoja IT- ja OT-järjestelmien välillä. Perinteisesti OT-järjestelmät olivat suljettuja ja eristettyjä ulkoisista verkoista. Nyt älykkäiden sensoreiden, pilvipalveluiden ja liitettyjen laitteiden myötä nuo rajat ovat hälvenemässä — tarjoten uusia mahdollisuuksia, mutta myös uusia riskejä.
Autonomian paradoksi
Autonomian paradoksi piilee ihmiskontrollin ja koneellisen itsenäisyyden välisessä tasapainossa. Autonomiset järjestelmät on suunniteltu toimimaan ilman jatkuvaa ihmisen väliintuloa, tavoitteenaan lisätä tehokkuutta ja reagointikykyä. Tämä kuitenkin siirtää ihmisen sivurooliin, jolloin suora valvonta vähenee. Samalla tekoälyjärjestelmät muuttuvat jatkuvasti — tavoilla, joita on vaikea ymmärtää tai ennustaa. Monet turvatoimet perustuvat vielä vanhoihin oletuksiin, jotka eivät enää vastaa nykyaikaisen tekoälyn dynaamista luonnetta. Näin ollen autonomia, jonka oli tarkoitus parantaa turvallisuutta, voi päinvastoin lisätä riskejä ja epävarmuutta.
Tomi Engdahl says:
Olemme siirtymässä aikaan, jossa autonomiset päätökset vaikuttavat fyysiseen maailmaan – koneet säätelevät sähkövirtoja, kemikaalipitoisuuksia ja robottien liikkeitä. Hallinnan illuusio on vaarallinen – ei siksi, että autonomia epäonnistuu, vaan siksi, että se epäonnistuu hiljaa ja joskus tuhoisasti.
Tomi Engdahl says:
Tekoäly on WWW:lle sama kuin roskaposti sähköpostille. Tuohon verrattuna se kirjastojen waretus oli vielä kesyä, ei siis kulutettu uhrien laskentatehoa.
AI web crawlers are destroying websites in their never-ending hunger for any and all content
But the cure may ruin the web….
https://www.theregister.com/2025/08/29/ai_web_crawlers_are_destroying/
Opinion With AI’s rise, AI web crawlers are strip-mining the web in their perpetual hunt for ever more content to feed into their Large Language Model (LLM) mills. How much traffic do they account for? According to Cloudflare, a major content delivery network (CDN) force, 30% of global web traffic now comes from bots. Leading the way and growing fast? AI bots.
Cloud services company Fastly agrees. It reports that 80% of all AI bot traffic comes from AI data fetcher bots. So, you ask, “What’s the problem? Haven’t web crawlers been around since 1993 with the arrival of the World Wide Web Wanderer in 1993?” Well, yes, they have. Anyone who runs a website, though, knows there’s a huge, honking difference between the old-style crawlers and today’s AI crawlers. The new ones are site killers
Fastly warns that they’re causing “performance degradation, service disruption, and increased operational costs.” Why? Because they’re hammering websites with traffic spikes that can reach up to ten or even twenty times normal levels within minutes.
Moreover, AI crawlers are much more aggressive than standard crawlers. As the InMotionhosting web hosting company notes, they also tend to disregard crawl delays or bandwidth-saving guidelines and extract full page text, and sometimes attempt to follow dynamic links or scripts.
The result? If you’re using a shared server for your website, as many small businesses do, even if your site isn’t being shaken down for content, other sites on the same hardware with the same Internet pipe may be getting hit. This means your site’s performance drops through the floor even if an AI crawler isn’t raiding your website.
Even large websites are feeling the crush. To handle the load, they must increase their processor, memory, and network resources. If they don’t? Well, according to most web hosting companies, if a website takes longer than three seconds to load, more than half of visitors will abandon the site. Bounce rates jump up for every second beyond that threshold.
So when AI searchbots, with Meta (52% of AI searchbot traffic), Google (23%), and OpenAI (20%) leading the way, clobber websites with as much as 30 Terabits in a single surge, they’re damaging even the largest companies’ site performance.
Now, if that were traffic that I could monetize, it would be one thing. It’s not. It used to be when search indexing crawler, Googlebot, came calling
AI searchbots? Not so much. AI crawlers don’t direct users back to the original sources. They kick our sites around, return nothing, and we’re left trying to decide how we’re to make a living in the AI-driven web world.
For example, Perplexity has been accused by Cloudflare of ignoring robots.txt files. Perplexity, in turn, hotly denies this accusation
There are efforts afoot to supplement robots.txt with llms.txt files. This is a proposed standard to provide LLM-friendly content that LLMs can access without compromising the site’s performance. Not everyone is thrilled with this approach, though, and it may yet come to nothing.
In the meantime, to combat excessive crawling, some infrastructure providers, such as Cloudflare, now offer default bot-blocking services to block AI crawlers and provide mechanisms to deter AI companies from accessing their data. Other programs, such as the popular open-source and free Anubis AI crawler blocker, just attempt to slow down their visits to a, if you’ll pardon the expression, a crawl.
In the arms race between all businesses and their websites and AI companies, eventually, they’ll reach some kind of neutrality. Unfortunately, the web will be more fragmented than ever. Sites will further restrict or monetize access. Important, accurate information will end up siloed behind walls or removed altogether.
Tomi Engdahl says:
It’s no longer a hypothetical: Anthropic has discovered a hacker using its AI chatbot to plan and execute a large-scale data extortion campaign that targeted 17 organizations last month.
Read more at PCMag
bit.ly/462n0FQ
Anthropic Warns of Hacker Weaponizing Claude AI Like Never Before
The hacker ‘used AI to what we believe is an unprecedented degree’ by harnessing Claude to automate large parts of the data extortion campaign, Anthropic says.
https://uk.pcmag.com/ai/159759/anthropic-warns-of-hacker-weaponizing-claude-ai-like-never-before?fbclid=IwVERDUAMisXtleHRuA2FlbQIxMAABHrA56_3ddpHCBl-kKcw_WeQdPb58aws_XmAsoPqfhZi1DlyAzevrVdjAYY0w_aem_wx9RunK7D61DM9FH8g85vw
Tomi Engdahl says:
Synkkä ennustus tekoälystä toteutui
Pahempaa on luvassa, tekoäly-yhtiö ennustaa.
Synkkä ennustus tekoälystä toteutui
https://www.is.fi/digitoday/tietoturva/art-2000011464872.html
Yksi tietoturva-asiantuntijoiden ennuste, tekoälyn kehittämä automatisoitu kiristysohjelma, on toteutunut. Asiasta kertoo Claude-chatbotin kehittäjä, tekoäly-yhtiö Anthropic blogissaan.
Hyökkääjä käytti Claude-chatbotin ”vibe coding” -ominaisuutta, jossa hän loi tietokoneohjelman kirjoittamatta itse koodia. Hän kuvaili, mitä hän haluaa ohjelman tekevän, ja tekoäly toteutti sen.
Lopputuloksena oli täysin automatisoitu prosessi, jossa tekoälyn kirjoittama ohjelma etsi kohteet, murtautui niihin, varasti tietoja ja analysoi ne sekä lopuksi kirjoitti jopa lunnasvaatimukset.
Lunnasvaatimukset perustuivat tekoälyn analyysiin yrityksiltä varastetuista taloustiedoista. Kiristyssummat vaihtelivat 75 000:n ja 500 000 dollarin (64 000:n ja 426 000 euron) välillä.
Kohteita oli ainakin 17. Yrityksiä ei nimetty, mutta niiden joukossa oli ainakin yksi puolustusalan yritys, rahalaitos ja useampi terveydenhuollon yritys.