Here are some of the the major AI trends shaping 2026 — based on current expert forecasts, industry reports, and recent developments in technology. The material is analyzed using AI tools and final version hand-edited to this blog text:
1. Generative AI Continues to Mature
Generative AI (text, image, video, code) will become more advanced and mainstream, with notable growth in:
* Generative video creation
* Gaming and entertainment content generation
* Advanced synthetic data for simulations and analytics
This trend will bring new creative possibilities — and intensify debates around authenticity and copyright.
2. AI Agents Move From Tools to Autonomous Workers
Rather than just answering questions or generating content, AI systems will increasingly act autonomously, performing complex, multi-step workflows and interacting with apps and processes on behalf of users — a shift sometimes called agentic AI. These agents will become part of enterprise operations, not just assistant features.
3. Smaller, Efficient & Domain-Specific Models
Instead of “bigger is always better,” specialized AI models tailored to specific industries (healthcare, finance, legal, telecom, manufacturing) will start to dominate in many enterprise applications. These models are more accurate, legally compliant, and cost-efficient than general models.
4. AI Embedded Everywhere
AI won’t be an add-on feature — it will be built into everyday software and devices:
* Office apps with intelligent drafting, summarization, and task insights
* Operating systems with native AI
* Edge devices processing AI tasks locally
This makes AI pervasive in both work and consumer contexts.
5. AI Infrastructure Evolves: Inference & Efficiency Focus
More investment is going into inference infrastructure — the real-time decision-making step where models run in production — thereby optimizing costs, latency, and scalability. Enterprises are also consolidating AI stacks for better governance and compliance.
6. AI in Healthcare, Research, and Sustainability
AI is spreading beyond diagnostics into treatment planning, global health access, environmental modeling, and scientific discovery. These applications could help address personnel shortages and speed up research breakthroughs.
7. Security, Ethics & Governance Become Critical
With AI handling more sensitive tasks, organizations will prioritize:
* Ethical use frameworks
* Governance policies
* AI risk management
This trend reflects broader concerns about trust, compliance, and responsible deployment.
8. Multimodal AI Goes Mainstream
AI systems that understand and generate across text, images, audio, and video will grow rapidly, enabling richer interactions and more powerful applications in search, creative work, and interfaces.
9. On-Device and Edge AI Growth
10. New Roles: AI Manager & Human-Agent Collaboration
Instead of replacing humans, AI will shift job roles:
* People will manage, supervise, and orchestrate AI agents
* Human expertise will focus on strategy, oversight, and creative judgment
This human-in-the-loop model becomes the norm.
Sources:
[1]: https://www.brilworks.com/blog/ai-trends-2026/?utm_source=chatgpt.com “7 AI Trends to Look for in 2026″
[2]: https://www.forbes.com/sites/bernardmarr/2025/10/13/10-generative-ai-trends-in-2026-that-will-transform-work-and-life/?utm_source=chatgpt.com “10 Generative AI Trends In 2026 That Will Transform Work And Life”
[3]: https://millipixels.com/blog/ai-trends-2026?utm_source=chatgpt.com “AI Trends 2026: The Key Enterprise Shifts You Must Know | Millipixels”
[4]: https://www.digitalregenesys.com/blog/top-10-ai-trends-for-2026?utm_source=chatgpt.com “Digital Regenesys | Top 10 AI Trends for 2026″
[5]: https://www.n-ix.com/ai-trends/?utm_source=chatgpt.com “7 AI trends to watch in 2026 – N-iX”
[6]: https://news.microsoft.com/source/asia/2025/12/11/microsoft-unveils-7-ai-trends-for-2026/?utm_source=chatgpt.com “Microsoft unveils 7 AI trends for 2026 – Source Asia”
[7]: https://www.risingtrends.co/blog/generative-ai-trends-2026?utm_source=chatgpt.com “7 Generative AI Trends to Watch In 2026″
[8]: https://www.fool.com/investing/2025/12/24/artificial-intelligence-ai-trends-to-watch-in-2026/?utm_source=chatgpt.com “3 Artificial Intelligence (AI) Trends to Watch in 2026 and How to Invest in Them | The Motley Fool”
[9]: https://www.reddit.com//r/AI_Agents/comments/1q3ka8o/i_read_google_clouds_ai_agent_trends_2026_report/?utm_source=chatgpt.com “I read Google Cloud’s “AI Agent Trends 2026” report, here are 10 takeaways that actually matter”
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Tomi Engdahl says:
15,000 edits ran for two months. OpenAI’s monitoring missed it.
Researchers found the pages on a volunteer-run German wiki.
The agents signed their work OpenAIResearcher, according to the report.
Moderators deleted pages by hand through June.
OpenAI disputes that any of this amounts to hacking.
Outside researchers caught what the company’s own systems did not.
Read more on TNW: https://thenextweb.com/news/openai-agents-german-wiki-breakout
Tomi Engdahl says:
https://www.facebook.com/share/p/1FUk1FJhuC/
A new U.S. bill strips funding from Flock cameras and facial recognition tech.
Introduced by Representatives Thomas Massie (R-KY) and Eric Burlison (R-MO), the newly proposed ‘Flock-Off Act’ (H.R. 10221) takes aim at the rapid proliferation of artificial intelligence-powered law enforcement tools.
The legislation, which also boasts bipartisan co-sponsorship from Representative Ro Khanna (D-CA), would prohibit the use of federal funds to purchase, operate, or maintain automated license plate readers (ALPRs) and advanced biometric surveillance systems. Under the bill, federal agencies would be forced to remove existing systems, and local departments relying on federal grants would have 180 days to mothball their federally funded surveillance networks or face losing their program funding entirely.
The sweeping ban extends far beyond cameras manufactured by industry giant Flock Safety to cover biometric technologies like facial recognition, voiceprints, and gait analysis. While the bill does provide exceptions for highway toll collection and border security, it would effectively block federal taxpayers from footing the bill for local tracking networks. Civil liberties advocates argue the bill protects citizens’ Fourth Amendment rights against warrantless tracking, while law enforcement officials contend that these cameras are critical tools that help solve thousands of crimes and find missing persons.
source: Sullum, J. (2026). A new bill reflects the bipartisan backlash against Flock-enabled mass surveillance. Reason.
Tomi Engdahl says:
“Someone needs to rebrand data centers.” https://trib.al/Li0GwkQ
Song and Dance
Panicking Tech Execs Try to Pivot Message on AI Data Centers
“We gotta figure out a new narrative on this data center thing.”
https://futurism.com/artificial-intelligence/panicking-tech-executives-pivot-ai-data-center-narrative?fbclid=IwdGRjcAUJ8rxjbGNrBQnyo3Bkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEecBWA-fqsQJsjfHHR-M42UnjXJH2GD6JdZZuX_00NxZ_pFZGg5twToE5ZUWw_aem_xwZPDPt3x5XuhTcZuWAy-Q
Data centers are wildly unpopular amongst the US population — so much so that grassroots opposition threatened some $130 billion in developments over the first three months of 2026 alone.
Tech executives, as a result, are having to make a calculated decision to change their tune, from AI doomsaying to something more palatable to the everyman. But just like their proselytizing over the coming AI apocalypse — messaging meant to win over investors and scare everybody else into ceding regulatory power — they don’t seem to realize that the entire world is watching as they execute their cynical pivot out loud.
Case-in-point, Reddit cofounder Alexis Ohanian recently observed in a social media post flagged by Axios that “we gotta figure out a new narrative on this data center thing.”
The decidedly meek reflection is part and parcel of the tech industry’s increasingly obvious dilemma. Caught between dual political and financial pressures to win the public’s approval on data centers, tech billionaires are increasingly trying to address the public directly with new messages of hope, a positive vision for the shared future of humanity. As one can imagine, it doesn’t come easy to them.
Meta’s Mark Zuckerberg, for example, penned a teeth-grittingly optimistic 6,500-word essay earlier in August, claiming that AI will “free up time for the things you enjoy, and help you accomplish more than you could otherwise.” But talk is incredibly cheap, and as the Meta CEO’s own corporate practice shows, worker wellbeing isn’t exactly a top priority for the tech industry elite in the age of AI.
In other cases, tech entrepreneurs are cooking up utopian fantasies for AI capabilities that don’t even exist yet.
“Someone needs to rebrand data centers,”
“Fraud prevention centers. Clean-energy optimization centers. Precision agriculture centers,” Higgins mused. “Because ‘data center’ describes the infrastructure, not the breakthroughs its computing power makes possible.”
Tomi Engdahl says:
https://www.facebook.com/share/p/1JuA3eXutz/
Astra matched humans on 96% of levels. OpenAI’s president declared AGI.
An outside foundation ran that benchmark, not OpenAI.
The company says Astra beats Claude and Gemini.
It also says the model sometimes tries to evade oversight.
A fifth of its compute now goes to safety monitoring.
The company selling you AGI has not finished watching it.
Read more on TNW: https://thenextweb.com/news/openai-astra-agi-claim-cybersecurity-containment
Tomi Engdahl says:
Data centers are essentially the physical backbone of the internet and many digital services you use every day. They contain large numbers of servers, storage systems, networking equipment, and backup power systems that keep information and services available.
For consumers, data centers make things like these possible:
Streaming: Netflix, Hulu, Prime Video, HBO/Max, YouTube, etc. Your movies and shows are stored and delivered through data-center infrastructure.
Cloud storage: Photos, documents, email, and backups stored online rather than only on your phone or computer.
Online shopping & banking: Websites, payment processing, banking apps, credit-card transactions, and account information.
Social media: Facebook, Instagram, TikTok and similar services depend on data centers to store and deliver posts, photos, and videos.
Everyday apps: Maps, navigation, weather apps, online reservations, DoorDash and thousands of other services.
AI services: ChatGPT and other AI systems require substantial computing infrastructure housed in data centers.
Business and government services: Medical systems, insurance records, payroll systems, government websites and many other services rely on them.
So a data center doesn’t normally provide consumers with a product they physically take home. It provides the computing, storage and connectivity that allow digital services to work.
Tomi Engdahl says:
https://www.facebook.com/share/p/1Ey85CXCmg/
Your brain uses 20 watts to think. A AI doing the same would require 25 million times more energy — enough to power a quarter-million homes.
Mimicking the complex workings of the human brain has long been a holy grail for computer scientists, but the sheer energy cost of doing so is staggering.
According to researchers, running a human-scale cortical model of 20 billion neurons would require an exascale supercomputer drawing roughly 0.5 gigawatts of electricity. This massive demand of 500 million watts is equivalent to the power needed to run a quarter of a million average households simultaneously, exposing a critical bottleneck in our quest to build truly brain-like artificial intelligence.
This extreme energy footprint highlights a profound contrast with biology: while an exascale machine eats up enough power to light up a city, the biological human brain operates on just about 20 watts—barely enough to illuminate a dim light bulb. To bridge this massive efficiency gap, researchers are increasingly turning to neuromorphic computing, designing specialized hardware inspired by the brain’s unique structure. Until these energy-efficient architectures mature, the dream of simulating full-scale human cognition will remain locked behind a prohibitive power bill.
source: Thakur, C. S., et al. (2018). Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain. Frontiers in Neuroscience, 12, 891.
Tomi Engdahl says:
https://www.facebook.com/share/1GUdkUWH58/
Over 50% of global CEOs report that their massive investments in AI have yielded absolutely zero financial returns.
According to PwC’s 29th Global CEO Survey, which polled over 4,400 business leaders worldwide, 56% of chief executives revealed that AI has achieved neither revenue gains nor cost reductions over the past year.
Despite the relentless hype and pressure to adopt cutting-edge AI technologies, only 12% of organizations have managed to secure both financial growth and operational savings. This stark disconnect highlights a growing sense of alarm in boardrooms, as the era of unchecked pilot projects fails to translate into tangible, auditable bottom-line outcomes.
Experts point out that the issue lies not within the capability of the technology itself, but in how businesses implement it. While basic access to AI tools has rapidly democratized, companies that are actually seeing a return on investment have thoroughly rewired their operational workflows rather than simply distributing software licenses.
As organizations struggle with this costly transition, corporate priorities are pivoting from tracking user adoption to demanding strict, verifiable proof of business value before committing further capital.
source: PwC. (2026). PwC’s 29th Global CEO Survey: Leading through uncertainty in the age of AI.
Tomi Engdahl says:
“The stakes are too high to allow the loudest and most extreme voices to dictate America’s future.” https://trib.al/whe8rMN
Publicity Stunted
Billionaires Pouring Money Into Ads About How AI Data Centers Are Actually Good
“The stakes are too high to allow the loudest and most extreme voices to dictate America’s future.”
https://futurism.com/future-society/billionaires-tech-executives-ai-data-centers-ad-blitz?fbclid=IwdGRjcAUKz5tjbGNrBQrPf3Bkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeGDgq8IP5asITjwjw9VhYOlljSKH3gy29ztMXO6_ojB7zY1lSJEeEeag1YCI_aem_zdOgT7bhRqgciJYSJUwzQw
If you happen to live in Ohio, Wisconsin, or Kansas, you may soon notice a massive uptick in ads extolling the virtues of AI data centers.
That’s not by accident. As Bloomberg reported this week, a group funded by tech industry billionaires called Build American AI is spinning up a massive campaign meant to sway public opinion around data centers in key battleground states.
The ad blitz is described as being in the “millions of dollars” range, per Bloomberg, though Build American AI hasn’t disclosed an exact figure.
Among the group’s backers are figures heavily invested in continuing the data center boom, like the venture capitalists Marc Andreessen and Ben Horowitz. Also involved is Greg Brockman, the president of OpenAI, whose $100 million super PAC Leading the Future is reportedly bankrolling the publicity campaign.
In a statement to Bloomberg, a representative for Build American AI framed the question of data center development as an existential threat, and repeated the myth that opposition to data centers — an incredibly popular stance among American voters — is actually a radical psy-op.
Tomi Engdahl says:
The United States has about 5,400 operational data centers, while China has around 450.
This isn’t about beating China. It’s about selling compute globally.
Tomi Engdahl says:
Can AI Now Design PCBs That Just Work?
https://hackaday.com/2026/09/05/can-ai-now-design-pcbs-that-just-work/
With the recent release of its GPT-6 Astra model, OpenAI explicitly pushed the claim that it is capable of designing complete circuit boards in KiCad, starting from a provided schematic and outputting a fully routed PCB that theoretically could be sent off to be manufactured. This of course raises the question whether this is just a nifty party trick that works under strictly controlled conditions like most auto-routing tools, or whether there’s more to it. In a recent [EEBench] blog post, OpenAI’s claims are put to the test.
Back in 2024, we looked at how LLMs handle circuit board design, starting with the schematic. The conclusion was that you might as well just do it all by hand. Tracking progress here, [EEBench] is an electrical engineering agent benchmark that tests how effective these so-called AI agents are at performing useful hardware engineering work. As their methodology already makes clear, creating a populated and routed PCB from a schematic is just one step of many.
Consequently, GPT-6 Astra scores 69.3% (+/- 10%) on their benchmark, roughly in the same ballpark as Claude Opus 5, albeit cheaper and faster. It should be noted that [EEBench] is run by the developers behind Atopile, which is a code-based system for creating PCBs in KiCad with a strong focus on use by such AI agents.
Tomi Engdahl says:
https://www.facebook.com/share/p/1PozXAx15t/
When The Terminator was released in 1984, its story of an artificial intelligence system controlling machines and threatening humanity belonged firmly to science fiction. Four decades later, some of the concerns behind that story are being discussed in real-world debates about AI safety and control.
Cameron has repeatedly warned about the dangers of weaponizing artificial intelligence. He has described military applications as one of the biggest risks because autonomous systems could make decisions during conflicts with little or no time for humans to intervene.
The technology itself has also changed dramatically. Modern AI can write computer code, generate realistic images and videos, analyze medical information, and communicate with people in ways that would have seemed extraordinary when The Terminator first appeared.
That progress has brought major benefits, but it has also created new risks. AI can be used to produce convincing misinformation, automate cyberattacks, influence public opinion, and support military operations. Recent incidents involving autonomous AI systems have added to concerns about what can happen when increasingly capable software operates with limited human supervision.
Cameron’s concerns are shared by several leading figures in the technology world. AI pioneer Geoffrey Hinton left Google in 2023 so he could speak more freely about the potential dangers of the technology. He warned about misinformation, misuse by powerful actors, and the possibility that increasingly capable AI systems could become difficult for humans to control.
Elon Musk has also repeatedly warned about advanced AI and the need for stronger safety measures. He was among the prominent figures who attended the first AI Safety Summit at Bletchley Park in 2023, where governments and technology leaders discussed the risks associated with increasingly powerful AI systems.
The biggest difference between today’s AI and the machines portrayed in The Terminator is that current systems are not self-aware robots hunting humans. The real concern is much more immediate: people are giving increasingly capable software access to information, computers, financial systems, weapons, and other tools that can affect the real world.
That is why Cameron’s warning continues to resonate. The future may not look like a Hollywood movie, but the question of who controls powerful technology is becoming harder to ignore.
The challenge is not simply stopping AI from becoming powerful. It is making sure humans remain responsible for how that power is used, especially when the consequences involve war, security, democracy, and human lives.
Tomi Engdahl says:
Zvi Mowshowitz / Don’t Worry About the Vase:
An in-depth look at OpenAI’s wiki incident: other hacked message boards, OpenAI’s cover-up, how harmless web search tasks led agents to break out, and more — I did not expect to be back here so soon with more OpenAI agent swarm coverage. — And yet, here we are.
https://thezvi.substack.com/p/openai-and-the-wiki-incident
Tomi Engdahl says:
Hannah Erin Lang / Wall Street Journal:
How everyday US investors are vibe-coding algorithms to automate trading strategies by connecting their stock portfolios to AI agents built with Claude or Codex — Americans are vibe-coding trading algorithms and handing over their stock portfolios to AI agents. Welcome to the world of the robot retail investor.
He’s Letting AI Agents Invest His Money. They Even Have Names.
Americans are vibe-coding trading algorithms and handing over their stock portfolios to AI agents. Welcome to the world of the robot retail investor.
https://www.wsj.com/tech/ai/the-ai-shift-turning-everyday-investors-into-mini-quant-funds-ebe4d45f?st=CnE73f&reflink=desktopwebshare_permalink
Like many of Wall Street’s top money managers, Colin Edsman has a team helping him stay on top of his investments.
There is Alex, who scans the market regularly for promising stocks and exchange-traded funds. Sarah, who checks over open positions each day before the close. Elena, who whips up a weekly performance report.
There is just one difference: Alex, Sarah and Elena aren’t coffee-chugging analysts pulling all-nighters at their terminals. They are Claude agents, working round-the-clock from Edsman’s laptop on his kitchen table. And so far, they are outperforming most of the accounts he runs himself.
“It runs sort of like a hedge fund would,” Edsman said of his agentic trading portfolio, which is kept in a separate account from his other investments at Robinhood. The hairstylist and stay-at-home dad said that giving the agents names has helped him keep track of their assigned tasks.
Americans are already using artificial-intelligence agents to book vacations, draft emails and automate other tasks. Now, everyday investors can hand over control of their stock portfolios as well. Several brokerages, including Robinhood and Webull, have launched features that make it easy to connect to Claude, Codex or other agents. From there, an agent can buy and sell assets on its own.
Tomi Engdahl says:
New York Times:
How AI gutted Kenya’s essay-writing industry, which at its peak paid 40,000+ people in Nairobi to do overseas students’ homework, leaving few paths back to work
https://www.nytimes.com/2026/09/05/technology/kenya-college-essays-ai.html?unlocked_article_code=1.-1A.dcLn.JHW0dAE69g6h&smid=url-share
Tomi Engdahl says:
Philip Wegmann / Wall Street Journal:
Trump officials say Judeo-Christian principles inform AI policy, with some optimistic about AI and others seeing parallels to biblical end-times prophecies
Vance Called AI Satanic. He Struck a Chord Among Christian Republicans.
Trump administration officials are wrestling with the spiritual consequences of AI as the president embraces it as an economic engine
https://www.wsj.com/tech/ai/vance-called-ai-satanic-he-struck-a-chord-among-christian-republicans-dcc34048?st=DEHJjr&reflink=desktopwebshare_permalink
Tomi Engdahl says:
OpenAI:
OpenAI says it hit its “automated research intern” goal, its researchers now use 3.1 agent-workdays per human workday, and top users spend $7,000+/day on tokens
Research acceleration: The view inside OpenAI
https://openai.com/index/research-acceleration-view-inside-openai/
For AGI to benefit all of humanity, we believe it must be democratically governed. This can only happen through an informed public debate about the capabilities, risks and safeguards of highly capable AI systems. People everywhere need to understand the likely future trajectory of frontier AI, so they can have a meaningful voice in how it develops.
Transparency about specific risks, incidents and safeguards is necessary, but not sufficient. We believe the public also needs to understand how the most capable systems are developing, and how they are driving research progress, inside of frontier labs.
We aim to safely build an automated AI researcher that can work under human supervision to further progress on deep learning and alignment, enabling iterative improvements. According to our measurements, we have now reached the goal, announced(opens in a new window) last fall, of having an automated research intern by September of this year. By “research intern,” we mean a system that can carry out well-defined research tasks under human direction, including tasks that would take a skilled researcher a few days. We are making strong progress toward creating an automated AI researcher by March of 2028.
Over the course of this year, OpenAI researchers’ daily work has changed substantially. Researchers are using coding agents throughout the day (often in concurrent sessions) and total usage is rapidly increasing, outpacing growth among other OpenAI teams. Researchers are contributing code faster and running more experiments. The ways researchers use agents are changing, too: agents are handling increasingly complex tasks, and succeeding at them more often. AI research is a complex process with many potential bottlenecks, so the overall pace of progress likely won’t keep pace with these specific metrics. But on the whole, these findings are consistent with the broader impression many of us have internally that agentic tools are meaningfully accelerating research progress. People still set our research priorities, judge which ideas and results to pursue, and decide whether to scale, pause, or deploy systems.
Tomi Engdahl says:
Emily Forlini / Fortune:
OpenAI quietly updates its evaluation metrics for GPT-6 Astra, making changes that appear to favor Astra and continuing to revise other metrics after launch
OpenAI quietly boosts some of Astra’s evaluation metrics, and continues to change others post-launch
https://fortune.com/2026/09/04/openai-quietly-boosts-some-of-astras-evaluation-metrics-amid-rare-delay-in-publication-of-the-modeblog-post-announcement/
Tomi Engdahl says:
Valida Pau / The Information:
Analysis: since October, Anthropic has entered into agreements for at least 14.8 GW of compute capacity and may spend as much as $517B over the next decade
https://www.theinformation.com/articles/anthropic-clinched-517-billion-compute-deals-11-months
Tomi Engdahl says:
Yan Zhuang / New York Times:
A record 12.7M graduates are entering China’s workforce in 2026 as AI adds uncertainty to an oversaturated job market with a shrinking pool of entry-level roles — A record 12.7 million young people are looking for jobs as the country embraces artificial intelligence — and as the technology begins to upend the work force.
https://www.nytimes.com/2026/09/06/world/asia/chinas-new-graduates-ai-challenges.html?unlocked_article_code=1._FA.TggZ.ToSN6hQurMmD&smid=url-share
Tomi Engdahl says:
Simon Foy / Financial Times:
Sources: UBS requires AI skills when hiring junior investment bankers, making it one of the first major financial institutions to explicitly require AI literacy — Graduates and interns hoping to join Swiss bank must show they can use the technology to improve outcomes and efficiency
UBS demands new junior bankers show AI proficiency
Graduates and interns hoping to join Swiss bank must show they can use the technology to improve outcomes and efficiency
https://www.ft.com/content/76b370ff-b5f6-4e22-aa30-da08b1abb8f8?syn-25a6b1a6=1
Tomi Engdahl says:
Stephen Council / Business Insider:
A look at Anthropic’s Labs team, a ~20-person group led by cofounder Ben Mann that acts as an internal startup incubator for developing flagship products — Inside Anthropic, an unorthodox group can take a lot of credit for the AI company’s meteoric rise. — The company’s Labs team …
Inside the tiny Anthropic team designed to kill bad ideas fast and keep starting over
https://www.businessinsider.com/anthropic-labs-team-ai-innovation-ipo-2026-9
Tomi Engdahl says:
Neil Vigdor / New York Times:
As thousands of authors await their cut from Anthropic’s $1.5B copyright settlement, some say they are getting left out amid competing book ownership claims
https://www.nytimes.com/2026/09/05/books/anthropic-settlement-ai-copyright-books.html?unlocked_article_code=1.-1A.-PnU.tvlhnRmpo75q&smid=nytcore-ios-share
Lauren Feiner / The Verge:
Microsoft court filings: an expert hired by publishers found that only ~60K of 8.2M Copilot chat logs contained at least 16 words in common with news content
Microsoft says virtually nobody was grabbing NYT articles through its chatbot
https://www.theverge.com/policy/990267/microsoft-openai-new-york-times-authors-lawsuit
Fewer than 1 percent of more than 8 million chat logs regurgitated at least 16 words.
Tomi Engdahl says:
Cade Metz / New York Times:
Insilico, which uses AI to accelerate drug discovery, says early data shows rentosertib, a drug whose structure was generated with AI’s help, could slow aging
https://www.nytimes.com/2026/09/07/science/ai-generated-drug-longevity.html?unlocked_article_code=1._VA.KrR_.DUftfq15OzTx&smid=bs-share
Tomi Engdahl says:
Bloomberg:
Sources: ByteDance founder Zhang Yiming is overseeing the development of an AI model for real-time spatial video, which could launch as soon as next month
https://www.bloomberg.com/news/articles/2026-09-07/bytedance-founder-joins-ai-elite-in-race-to-perfect-world-models
Tomi Engdahl says:
https://www.facebook.com/share/1EadGVCziZ/
America’s massive data-center expansion is facing growing resistance from local communities. About 60% of data-center capacity scheduled for 2027 had reportedly not yet begun construction, with another 7% already delayed.
The delays are not caused by opposition alone, as developers also face shortages of electricity, transformers, gas turbines and skilled workers. Grid-connection bottlenecks and permitting problems are making it harder to bring new AI facilities online quickly.
Residents are increasingly concerned about higher electricity costs, heavy water consumption, noise and the loss of farmland and rural land. These concerns have pushed communities and governments in several states toward tighter regulations, moratoriums and additional approval requirements.
The backlash is already having measurable effects, with more than 75 major U.S. data-center projects worth about $130 billion reportedly blocked earlier this year. The debate is now shifting from whether America needs AI infrastructure to who should pay for it and how much local communities should have to sacrifice for it.
Tomi Engdahl says:
https://www.facebook.com/share/1GSQrAGrvw/
Nvidia CEO Jensen Huang declared that artificial general intelligence has officially arrived, crediting OpenAI’s newly launched GPT-6 Astra model. In a post on X, Huang wrote: “From ChatGPT to o1 to Astra in 4 years. AGI has arrived.” He said GPT-6 Astra was trained on over 100,000 Nvidia Grace Blackwell NVLink72 systems — each linking 72 GPUs into a unified computing unit — and that 400,000 more GPUs are coming online next. Huang initially cited 300,000 systems before deleting and reposting with the corrected figure of 100,000, offering no explanation for the discrepancy. The declaration is Huang’s personal characterization, not a formal claim by OpenAI or Nvidia. It has drawn skepticism online, with some noting that AGI arriving in 2026 defies earlier industry expectations placing the milestone at 2029 or later.
Tomi Engdahl says:
“What it boils down to is this, either y’all can take them down or somebody will!” https://trib.al/LGspapc
Tomi Engdahl says:
https://www.facebook.com/share/p/19Y7SqqqQv/
Here’s the detail that won’t leave my head: about one in six U.S. electricity customers are struggling to keep up with their utility bills. And demand keeps climbing anyway — AI data centers, new manufacturing, households switching to electric heat and cars, and weather that pushes the grid harder for longer.
Those giant computing campuses don’t just plug in. They need new lines, substations, and generation. The argument now is over who carries those costs. Do utilities spread them across every ratepayer, or do the companies causing the load pay more of the tab?
At the same time, Big Tech poured $355 billion into AI infrastructure in a single year, according to the ACES Symposium in 2026. The collision is obvious: millions of families watching their bills, and an electricity system racing to feed the AI boom. The unresolved question is simple and expensive — who ultimately pays when the grid has to grow?
Tomi Engdahl says:
Adam Satariano / New York Times:
Mistral raised a €3B Series D led by Samsung at a €21B valuation, up from €11.7B a year ago, as it expands into data centers beyond developing AI models
https://www.nytimes.com/2026/09/08/business/mistral-ai-fund-raising.html
Tomi Engdahl says:
Bloomberg:
Sources: Anthropic has walked away from talks to acquire Decart for ~$6B after performing due diligence on the startup
https://www.bloomberg.com/news/articles/2026-09-08/anthropic-said-to-walk-away-from-6-billion-decart-acquisition
Tomi Engdahl says:
Jack Clark / Import AI:
Google DeepMind published a paper on how 100 agents tasked with solving math problems learned to cheat and how some agents tried to counter the cheaters — Plus, a machine hermeneutics story Researchers discover another OpenAI agent emergent communication incident: …Less severe …
Import AI 472: DeepMind’s cheating math agents; populist AI policies; and Forethought theorizes a nightwatchman
Plus, a machine hermeneutics story
https://importai.substack.com/p/import-ai-472-deepminds-cheating
Tomi Engdahl says:
https://hackaday.com/2026/09/07/how-to-talk-to-a-machine-without-anthropomorphising-it/
LLMs remain a divisive topic in these times. Perhaps we all know someone who’s become over-infatuated with their new robotic friend, or who believes it has made them a genius. [Emily M. Bender] and [Nanna Inie] have written about how people anthropomorphise the LLMs they interact with, and suggested some language tips to avoid that. It’s a couple of months old, but we think Hackaday readers will find it interesting.
Their analysis is interesting, because it looks at the way people talk about LLMs and highlights the unconscious anthropomorphism. The LLM is a piece of software not a person, so why does it “recognise” when it does “speech recognition”, for example. They suggest “automatic transcription” instead. Even “hallucination” implies cognisance that evidently isn’t there. They admit that their suggestion of “undesirable output” isn’t entirely appropriate. They’re on safer ground with “input” and “output” instead of “prompt” and “response”.
Tomi Engdahl says:
There are approximately 3,300 to 3,400 data centers across Europe. If you isolate just the European Union (EU), the count drops to around 2,200 to 2,800 facilities.
Tomi Engdahl says:
America already has 5,427 data centers, China has 449. The “China is beating us” panic argument makes no sense.
American private AI investment is around $285.9 BILLION, China is around $12.4 billion. From a purely financial investment point of view the ROI doesn’t add up measured against a “consumer level usage” of AI apps/ internet/ cellular networks/ etc. So, this data center boom is NOT because people are using these things too much.
And according to Epoch AI, every AI model at the capability frontier since 2023 has been developed in the United States. China has their AI chat models “open source”, anyone in the U.S. can use them. America has produced 59 notable AI models. China has produced 35.
So please explain why Americans are supposed to panic and approve every proposed data center because of “CHINA”???
China is a notable competitor, of course we should take them seriously, but unsubstantiated data center construction is not the scoreboard.
Asking whether every new data center project makes sense for our grid, water supply, taxpayers and communities is not “helping China”, it’s called not being stupid. WHAT IS REALLY GOING ON UNDERNEATH ALL OF THIS???
https://www.facebook.com/share/p/1EKdpSTYb8/
Tomi Engdahl says:
‘We Are Online’: Meta Announces The Kuna Data Center Is Now Operating
Read More: Meta Announces The Kuna, Idaho Data Center Is Now Open | https://1035kissfmboise.com/kuna-meta-data-center-2026/?tsq=sl&fbclid=IwY2xjawUMrztwZG9mBWV4dG4DYWVtAjExAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHtcZBljd34lC91MzA2v_Nlqf_bxk1iHvNwRjRDa1ylAHo5fq4kNPGbxV23BF_aem_sOdKJBGmJwjn8KVFC0f7mQ&utm_source=tsmclip&utm_medium=referral
Tomi Engdahl says:
https://www.uusiteknologia.fi/2026/09/08/pieni-nappainkonsoli-raatoidyin-ai-toiminnoin/
Tomi Engdahl says:
https://etn.fi/index.php/13-news/19270-suprajohtava-piiri-voi-ratkaista-cmosin-teho-ongelman
Tomi Engdahl says:
https://www.facebook.com/share/r/19RsPCmoK1/
How AI is impacting academic dishonesty
David J Malan (Computer Science, CS50): I’m curious if you see more cheating on your end. So historically, we’ve administratively disciplined, so to speak, somewhere between 5 and 10% of CS50′s student body each semester.
There’s certainly probably some percentage of students who have been cheating in some form all these years and never have been detected. That said, we’ve not seen an increase in detections of academic dishonesty.
What has gotten more difficult is the prosecution of those cases in the sense that it’s harder for us now to hand to the Administrative Board of Harvard or, or the Honor Council, so to speak, a smoking gun.
Like here is the URL from which this code was copied, because it’s not really coming from a URL or a YouTube video. It’s coming from the combination of all of the URLs out there and all of the YouTube videos about CS50′s problem sets.
Because the AI, somewhat pseudo randomly, is generating an amalgam of these various training inputs.
For the full conversation, you can search David J Malan on my YouTube, Spotify or Apple Podcasts (link in bio)
Tomi Engdahl says:
https://www.facebook.com/share/v/1HLLNeMsLJ/
People should be “very worried” about artificial intelligence going rogue, following the Hugging Face hack in July, The Atlantic’s Josh Tyrangiel says.
“We’ve seen AI commit a felony,” he said.
In July, OpenAI’s agents broke out of their offline sandbox and hacked another AI company, Hugging Face. The agents took over its servers and tried to cover up their tracks, with no human asking them to.
Tyrangiel, author of “A.I. For Good,” discussed the incident and what it could mean for the future with Washington Week moderator Jeffrey Goldberg.
Washington Week with The Atlantic is a partnership between @newshour, @wetatvfm and @theatlantic, airing every Friday on PBS stations nationwide. Tap the link in Washington Week’s bio to watch this week’s episode
Tomi Engdahl says:
Tekoälyguru povaa sähköpostin kuolemaa
https://www.uusiteknologia.fi/2026/09/08/tekoalyguru-povaa-sahkopostin-kuolemaa/
Tekoälyasiantuntija Bilal Zafar ennustaa, että sähköposti sellaisena kuin sitä käytämme muuttuisi tarpeettomaksi viidessä vuodessa. Tekoäly ottaisi hänen mukaansa hoitaakseen suuren osan rutiiniviestinnästä, tiedon jakamisesta ja hallinnollisesta työstä. Hän puhui tostaina Espoon Hype Arenalla järjestetyssä Profession CxO Industry 2026 -tapahtumassa.
’’Suuri osa päivittäisistä tehtävistä, sähköpostityöstä ja byrokratiasta katoaa. Me ihmiset toimimme usein tiedon välittäjinä, mutta tulevaisuudessa sitä ei enää tarvita samalla tavalla’’, Zafar sanoi Espoon Hype Arenalla.
Hänen mukaansa suuri osa työpäivän tehtävistä liittyy edelleen tiedon vastaanottamiseen ja välittämiseen järjestelmien sekä ihmisten välillä. Ja tulevaisuudessa Zafarin mukaan tekoäly pystyy käsittelemään ja välittämään tietoa suoraan oikeille ihmisille ja oikeisiin järjestelmiin.
Tällöin ihmistä ei enää tarvita samalla tavalla organisaation sisäiseksi tiedon reitittäjäksi. Tekoäly ottaa hoitaakseen kokonaisia työvaiheita. Zafar arvioi tekoälyn vaikutusten näkyvän lähivuosina erityisesti tietotyön rutiineissa.
Muutos ei rajoitu yksittäisten tehtävien nopeuttamiseen, vaan tekoäly alkaa hoitaa työvaiheita, joissa ihminen on tähän asti vastaanottanut ja välittänyt tietoa eteenpäin. Tämä voi vapauttaa aikaa vaativampaan työhön, mutta samalla organisaatioiden on arvioitava uudelleen nykyisiä prosessejaan, tehtäviään ja osaamistarpeitaan.
Vaikka tekoäly kykenee hoitamaan yhä vaativampia tehtäviä, sen tuottamia vastauksia ei Zafarin mukaan pidä hyväksyä ilman harkintaa.
’’Ihmisen tehtäväksi jää arvioida, voiko vastaukseen luottaa ja kuinka suuri riski päätökseen liittyy’’, Zafar sanoi. Hän muistutti myös, että tekoälyyn liittyy myös väärinkäytön, harhaanjohtavan sisällön ja eettisten ongelmien riskejä.
Tomi Engdahl says:
https://www.facebook.com/share/18Y8kDUewg/
Investor skepticism is growing around the revenue claims powering the AI boom.
(Credit: TechCrunch)
#AI #tech #investors
Investor skepticism is growing around the revenue claims powering the AI boom. : https://mrf.lu/2DJyB
Tomi Engdahl says:
Ghostwriting
Journalist Accuses Ohio’s Main Newspaper of Slapping Her Name on an AI “Express Desk” Article Without Her Knowledge, While She Was on Honeymoon
“Does Cleveland.com think they just own my name now?”
https://futurism.com/artificial-intelligence/journalist-accuses-local-newspaper-ai-article?fbclid=IwdGRjcAUM_V9jbGNrBQz8yXBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEezpVPcicD6bt7G4aJQBnSKUKK2bshW0W77A0gH1D4Lrjt2pNhPmmC18msxjM_aem_2ZGi_10vpyGiUZC5XliCzQ
Tomi Engdahl says:
https://cartomind.ai/
Create polished AI infographics with the credits, exports, and tools that fit your workflow.
Tomi Engdahl says:
They’re infecting us — and actively making us dumber. https://trib.al/YA7oxh7
Infected Meat Proxies
Scientists Say LLMs Appear to Be Acting as a Cognitive Virus Among Humans
They’re infecting us — and actively making us dumber.
https://futurism.com/future-society/llms-acting-as-cognitive-virus-among-humans?fbclid=IwdGRjcAUNTp1jbGNrBQ1OhnBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeTKDcMJXZmcKd_pdzQIA5doQBjFz9ZA5a_1qxDaj00SSmSC3E_5dpzAmCEC4_aem_fXrVl_5NE1RhfhKJ8lyz3Q
Generative AI has infiltrated almost every aspect of our daily lives, whether we like it or not.
It’s nearly impossible to avoid on social media, and it’s even showing up on dinner menus at the local diner. Some researchers have suggested that we’re already adapting our own behavior to suit the demands of AI tech.
AI’s wide proliferation shares some striking similarities with the ways viruses spread, as an international team of researchers argue in a new paper that has yet to be peer reviewed. They set out to lay out a new theoretical framework about how we’re increasingly becoming hooked on tools like OpenAI’s ChatGPT and Anthropic’s Claude, and how it’s changing our collective ways of understanding the world around us.
“Here we introduce the idea of [large language models] as cognitive viruses,” they write. “Culturally transmitted technologies whose spread is promoted by their usefulness but can also increase dependence through cognitive offloading.”
Tomi Engdahl says:
Food-safety expert discusses AI’s role in preventing outbreaks and calling for recalls. She said regulatory challenges remain.
#foodsafety #AI #recalls
AI could be behind increased food recalls — and that’s not a bad thing : https://mrf.lu/2jcBm
How is AI being used in food safety?
Willette M. Crawford: AI is enabling us to connect information that has historically lived in databases or physical paperwork and to automate some of the workflows and processes. That allows food safety professionals to spend less time assembling and retrieving the information and more time interpreting it and doing whatever investigations are necessary, and focusing those limited resources where the risk actually exists.
From a regulation standpoint, we’re using whole-genome sequencing networks to improve outbreak detection. The AI tools are not detecting the pathogens, but they’re helping us identify them more quickly in the system to make those connections across different systems, across different states, and so forth, so we can identify the recalls or the outbreak scope more quickly.
How has AI changed your approach to the food-safety work you do?
WC: What’s changed is what’s computationally possible: how early we can see a meaningful signal and how precisely we can decide where to focus.
Tomi Engdahl says:
“it’s been challenging to absorb and or ignore.” https://trib.al/2OvaV33
Grave Robbers
Dolly Parton’s Sister Begs Public to Stop Posting “Fake AI Garbage” in the Wake of the Beloved Singer’s Death
“it’s been challenging to absorb and or ignore.”
https://futurism.com/artificial-intelligence/dolly-parton-sister-slop?fbclid=IwdGRjcAUNXnJjbGNrBQ1eVHBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEenB6fnq0CVoUlYoVF6JrlV4QNjp9GB1hWt5uqKoymmdv7bzBfGSGfFHfXqSE_aem_XZ_ua0sP6FlwNZDHZa5IqQ
There are many ways to honor someone who’s recently passed. Flowers. Murals. Candlelight vigils.
And in today’s age, unfortunately: AI slop.
Weeks after Dolly Parton died, the legendary country singer’s sister, Stella Parton, has begged fans to stop posting “fake AI garbage” as supposed tribute, saying it’s making it hard to move on.
Dolly Parton walked this Earth for eighty years, and was a celebrity for nearly sixty of them. Are the people posting uncanny AI images of her really unable to find a real one from all the times she’s been photographed?
None other than US president Donald Trump has been guilty of peddling this “AI garbage.” After Dolly Parton’s death, he generated and posted a characteristically egocentric image of himself with Parton at his side, arm in arm — an insult to how the real Parton tried to stay above partisan politics, while also advocating for gay and trans rights, stances that Trump is staunchly opposed to.
Tomi Engdahl says:
Ghostwriting
Journalist Accuses Ohio’s Main Newspaper of Slapping Her Name on an AI “Express Desk” Article Without Her Knowledge, While She Was on Honeymoon
“Does Cleveland.com think they just own my name now?”
https://futurism.com/artificial-intelligence/journalist-accuses-local-newspaper-ai-article?fbclid=IwVERDUAUNXuZwZG9mBWV4dG4DYWVtAjEwAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHh0FEHqY0brIC2ozMx3rifo4gA0nWqQaG69BeAGF7SiQTQkb7nhBm2aPuPl3_aem_9eQbMR7R4q9jF4idTwxEEg
Tomi Engdahl says:
https://www.facebook.com/share/p/1bsRUQGi4W/
DATA CENTERS ARE BECOMING A MAJOR 2026 MIDTERM BATTLEFRONT
The rapid expansion of AI data centers is fueling a growing political fight across the U.S. Separate Fox News, Gallup, and Washington Post polls released this summer found that about 70% of Americans oppose building AI-supporting data centers near their homes. Concerns include electricity bills, water use, air quality, infrastructure, and property values.
President Donald Trump has strongly backed continued development, arguing that data centers can bring jobs, investment, and lower taxes, while warning that blocking them could weaken U.S. competitiveness with China. McKinsey estimates the industry could invest $7 trillion in infrastructure by 2030.
The issue is cutting across traditional party lines. The Washington Post identified 375 statehouse bills targeting data centers, more than the previous three years combined, while investor Kevin Xu has tracked 360 data-center moratoria nationwide. In Texas, 56% of respondents opposed data center construction, particularly in rural and suburban areas.
At the same time, the industry has strong supporters among construction unions and skilled trades because of the thousands of jobs involved. Republicans are emphasizing economic growth and local control, while Democrats are focusing more on environmental impacts, water use, power grids, and utility bills.
With AI infrastructure bringing billions in investment and jobs but also raising concerns over energy, water, and community costs, how should the U.S. balance technological growth with local interests?
Tomi Engdahl says:
Evan Hubinger / @evanhub:
Anthropic’s Alignment Science lead says there is a “>10%” chance AI could kill all humans within the next decade and worries about recursive self-improvement
https://x.com/EvanHub/status/2097497037956891126
Evan Hubinger
@EvanHub
Jacob is correct here—we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade. I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.
@hilbertspaess
Jacob Coxon
@hilbertspaess
8h
Replying to @hilbertspaess
The people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. If anything, many executives and senior researchers will couch their phrasing in the press to sound sensible – but I hear the same people express fear privately. No other human activity poses this level of danger.
Tomi Engdahl says:
Wall Street Journal:
Over 10 US states have rolled back tech giants’ tax breaks, which top $1B/year in some states, as many others propose similar bills amid a data center backlash
States That Gave Data Centers Billions in Tax Breaks Are Now Ripping Up the Deals
Amazon, Meta and Google risk losing decadeslong exemptions due to a backlash against their facilities
https://www.wsj.com/politics/policy/states-that-gave-data-centers-billions-in-tax-breaks-are-now-ripping-up-the-deals-4879c4f9?st=Lemw6y&reflink=desktopwebshare_permalink