Artificial intelligence is rapidly changing many aspects of how we work and live. (How many stories did you read last week about self-driving cars and job-stealing robots? Perhaps your holiday shopping involved some AI algorithms, as well.) But despite the constant flow of news, many misconceptions about AI remain.
AI doesn’t think in our sense of the word at all, Scriffignano explains. “In many ways, it’s not really intelligence. It’s regressive.”
IT leaders should make deliberate choices about what AI can and can’t do on its own. “You have to pay attention to giving AI autonomy intentionally and not by accident,”
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Tomi Engdahl says:
Machine vision software: Deep learning technology usage on the rise in machine vision software
https://www.vision-systems.com/articles/print/volume-22/issue-10/departments/technology-trends/machine-vision-software-deep-learning-technology-usage-on-the-rise-in-machine-vision-software.html?cmpid=enl_vsd_vsd_newsletter_2018-02-12&pwhid=6b9badc08db25d04d04ee00b499089ffc280910702f8ef99951bdbdad3175f54dcae8b7ad9fa2c1f5697ffa19d05535df56b8dc1e6f75b7b6f6f8c7461ce0b24&eid=289644432&bid=1999156
One of the most talked-about buzzwords of late is “deep learning,” which is an area of machine learning that enables computers to be trained and learn. Deep learning-which can be accomplished through architectures such as artificial neural networks-imitates the way the human brain works by processing data and creating patterns for use in decision making.
Major companies such as Google, Facebook, IBM, Intel, and Microsoft have made recent headlines regarding their involvement in the deep learning space, but as of late, some machine vision software companies have deployed the technology within their products, while others base their entire product on it.
Tomi Engdahl says:
How deep learning is enhancing machine vision
https://www.vision-systems.com/articles/print/volume-23/issue-1/features/how-deep-learning-is-enhancing-machine-vision.html?cmpid=enl_vsd_vsd_newsletter_2018-02-12&pwhid=6b9badc08db25d04d04ee00b499089ffc280910702f8ef99951bdbdad3175f54dcae8b7ad9fa2c1f5697ffa19d05535df56b8dc1e6f75b7b6f6f8c7461ce0b24&eid=289644432&bid=1999156
Developers increasingly apply deep learning and artificial neural networks to improve object detection and classification.
Tomi Engdahl says:
10 ways deep learning technology is being deployed today
https://www.vision-systems.com/articles/2017/12/10-ways-deep-learning-technology-is-being-deployed-today.html?cmpid=enl_vsd_vsd_newsletter_2018-02-12&pwhid=6b9badc08db25d04d04ee00b499089ffc280910702f8ef99951bdbdad3175f54dcae8b7ad9fa2c1f5697ffa19d05535df56b8dc1e6f75b7b6f6f8c7461ce0b24&eid=289644432&bid=1999156
Tomi Engdahl says:
How to spot a machine learning opportunity
https://enterprisersproject.com/article/2018/2/how-spot-machine-learning-opportunity?sc_cid=7016000000127ECAAY
Success with AI requires all kinds of people seek out machine learning opportunities. Learn how to create a team of AI sleuths
Tomi Engdahl says:
Job One for Quantum Computers: Boost Artificial Intelligence
https://www.quantamagazine.org/job-one-for-quantum-computers-boost-artificial-intelligence-20180129/
The fusion of quantum computing and machine learning has become a booming research area. Can it possibly live up to its high expectations?
Tomi Engdahl says:
Hypergiant helps big brands look beyond the AI buzzwords
https://techcrunch.com/2018/02/20/hypergiant-launch/?utm_source=tcfbpage&sr_share=facebook
Artificial intelligence and machine learning are phrases that get tossed around a lot these days, to the point where they’re starting to seem meaningless. In fact, Ben Lamm said he’s seen the problem firsthand at his chatbot startup Conversable.
“We kind of noticed this huge gap,” Lamm said. “Everybody has an emotional reaction to AI, everybody wants AI, nobody seems to know what that means.”
Tomi Engdahl says:
The AI era: 4 skills IT pros need to develop
https://enterprisersproject.com/article/2018/2/ai-era-4-skills-it-pros-need-develop?sc_cid=7016000000127ECAAY
Winning in the age of machine learning and artificial intelligence will require new skills. Here are four priorities for IT pros
The ability to understand and cultivate a sense of code, i.e., learning how certain coding concepts work together, will be a fundamental skill for success in the age of AI and ML.
Learn data anlaysis: Embracing data science will soon dovetail into an individual’s ability to successfully handle AI and machine learning.
Learn to decode buzzword bingo: At a very basic level, IT pros must understand the definitions of and differences between AI and ML. Possessing a broad, high-level knowledge of both technologies and which products/tools should be equipped with each
Become a better business partner: The rise in adoption and implementation of new technologies will require that IT professionals cultivate and maintain mutually beneficial relationships with business decision makers
Cultivating the skills necessary to succeed in the AI/ML age before these technologies have completely permeated the tech landscape will be important for IT pros’ job security and success in the coming years.
Tomi Engdahl says:
Why Self-Taught Artificial Intelligence Has Trouble With the Real World
By
JOSHUA SOKOL
February 21, 2018
https://www.quantamagazine.org/why-self-taught-artificial-intelligence-has-trouble-with-the-real-world-20180221/
The latest artificial intelligence systems start from zero knowledge of a game and grow to world-beating in a matter of hours. But researchers are struggling to apply these systems beyond the arcade.
Tomi Engdahl says:
Foundational Circuit Element to Neuromorphic Computing
https://spectrum.ieee.org/nanoclast/semiconductors/devices/memtransistor-forms-foundational-circuit-element-to-neuromorphic-computing
Computers that operate more like the human brain than computers—a field sometimes referred to as neuromorphic computing—have promised a new era of powerful computing.
While this all seems promising, one of the big shortcomings in neuromorphic computing has been that it doesn’t mimic the brain in a very important way. In the brain, for every neuron there are a thousand synapses—the electrical signal sent between the neurons of the brain. This poses a problem because a transistor only has a single terminal, hardly an accommodating architecture for multiplying signals.
Tomi Engdahl says:
Test Takes Rightful Place at Forefront of AI and Machine Learning
http://www.electronicdesign.com/test-measurement/test-takes-rightful-place-forefront-ai-and-machine-learning?NL=ED-003&Issue=ED-003_20180219_ED-003_349&sfvc4enews=42&cl=article_2_b&utm_rid=CPG05000002750211&utm_campaign=15417&utm_medium=email&elq2=b808b8d0462c4b0eb6a5bb61c2bf28c6
Applying AI and machine-learning principles to test and measurement is a good idea, but breaking down the data silos and making use of all available test data is challenging.
With all of the data being generated during test cycles, it’s logical to start applying appropriate analytics, artificial intelligence (AI), and machine-learning principles to act upon that data to get answers, insights, and improve processes and outcomes. It’s logical, but not easy. It turns out that there are quite a few challenges, not least of which is developing the right learning models, and then breaking down the data silos along the path through development, test, manufacturing, and in-field operation.
The benefits of tackling these problems include faster test times, more accurate channel modeling, less reliance on specific hardware, more integrated design and test processes and resources, faster scaling, and plenty of cost savings. As neural nodes learn faster and cloud-based, massively parallel computing takes hold, there’s also the possibility of finally getting to a point of predictability.
It’s always a difficult, iterative, process to use EDA tools to model high-speed channels and get correlation in the eye diagrams between the model and the measured channel or link. Beyond the physics of the actual interconnect, there’s the problem of missing models and the compute-intensive nature of the simulations.
Tomi Engdahl says:
Deconstructing Deep Learning
https://semiengineering.com/deconstructing-deep-learning/
What’s inside the package, what’s the goal, and how this technology is evolving.
Tomi Engdahl says:
Artificial intelligence could hunt for slow zones in overcrowded wireless networks: Researchers
http://www.cablinginstall.com/articles/pt/2018/02/artificial-intelligence-could-hunt-for-slow-zones-in-overcrowded-wireless-networks-researchers.html?cmpid=enl_cim_cim_data_center_newsletter_2018-02-22&pwhid=e8db06ed14609698465f1047e5984b63cb4378bd1778b17304d68673fe5cbd2798aa8300d050a73d96d04d9ea94e73adc417b4d6e8392599eabc952675516bc0&eid=293591077&bid=2012439
Using artificial intelligence to hunt for slow zones in overcrowded networks
http://augustafreepress.com/using-artificial-intelligence-hunt-slow-zones-overcrowded-networks/
We’re all connected — and not just in a yogic sense. By 2022, there will be 29 billion connected devices across the globe, according to a forecast from the June 2017 Ericsson mobility report. All of these devices will want a piece of the radio spectrum — the cluster of frequencies used by television, radio, and wireless signals — which will overcrowd radio bands.
Researchers like Lingjia Liu and Yang (Cindy) Yi, associate and assistant professors, respectively, in the Bradley Department of Electrical and Computer Engineering, are approaching the spectrum scarcity problem from various angles.
From techniques to tap unoccupied channels and improve spectrum efficiency to establishing protocols for sharing previously restricted bands, Liu, Yi, and their collaborators are exploring new ways to meet the skyrocketing demand. Liu is currently leading three projects totaling more than $2 million in funding.
Tomi Engdahl says:
Artificial intelligence poses risks of misuse by hackers, researchers say
https://www.reuters.com/article/us-cyber-tech/artificial-intelligence-poses-risks-of-misuse-by-hackers-researchers-say-idUSKCN1G503V
Rapid advances in artificial intelligence are raising risks that malicious users will soon exploit the technology to mount automated hacking attacks, cause driverless car crashes or turn commercial drones into targeted weapons, a new report warns.
“We all agree there are a lot of positive applications of AI,” Miles Brundage, a research fellow at Oxford’s Future of Humanity Institute. “There was a gap in the literature around the issue of malicious use.”
It reviews a growing body of academic research about the security risks posed by AI and calls on governments and policy and technical experts to collaborate and defuse these dangers.
The researchers detail the power of AI to generate synthetic images, text and audio to impersonate others online, in order to sway public opinion, noting the threat that authoritarian regimes could deploy such technology.
Late last year, so-called “deepfake” pornographic videos began to surface online, with celebrity faces realistically melded to different bodies.
“It happened in the regime of pornography rather than propaganda,”
Tomi Engdahl says:
Why AI on a chip is the start of the next IT explosion
https://gigaom.com/2018/02/20/why-ai-on-a-chip-is-the-start-of-the-next-it-explosion/
It’s game on in the AI-on-a-chip race. Alongside Nvidia’s successes turning Graphics Processing Units into massively performant compute devices (culminating in last year’s release of the ‘Volta’ V100 GPU), we have ARM releasing its ‘Project Trillium’ machine learning processor on Valentine’s Day and Intel making noises around bringing the fruits of its Nervana acquisition to market, currently at sample stage. Microsoft with Catapult, Google with its TPU — if you haven’t got some silicon AI going on at the moment, you are missing out. So, what’s going on?
Just because a CPU can process anything we throw at it, it won’t always be the best tool for the job.
We have CPUs as the de facto mechanism because the cost of fabrication has, traditionally been so great that we have gone for a one-size-fits-all solution. The downside, however. many bells and whistles we have attached to them, is that CPUs will have an overhead when they try to do things they weren’t designed for.
Traditionally, the answer has been to create different processors.
Ultimately, it’s easier to think of computer chips as combinations of task-specific modules, each designed around doing a certain kind of maths. We have now arrived at a point where the door is opening for those who want to design their own modules, or architect them into processors aimed at a specific purpose. So this isn’t about speed but architecture. In much the same way as home-grown app transformed the data management industry, so we can do the same with chips.
Tomi Engdahl says:
Neural networks help identify license plates for traffic control
https://www.vision-systems.com/articles/print/volume-23/issue-2/features/neural-networks-help-identify-license-plates-for-traffic-control.html?cmpid=enl_vsd_vsd_newsletter_2018-02-19&pwhid=6b9badc08db25d04d04ee00b499089ffc280910702f8ef99951bdbdad3175f54dcae8b7ad9fa2c1f5697ffa19d05535df56b8dc1e6f75b7b6f6f8c7461ce0b24&eid=289644432&bid=2007653
Combining off-the-shelf cameras and a PC running neural network software allows Singapore authorities to perform traffic monitoring and enforcement.
Andrew Wilson, European Editor
Automatic number plate recognition (ANPR) or license plate recognition (LPR) is a challenging task to perform in real-time. This is due to a number of reasons including the different types of license plates that need to be recognized, the varying lighting conditions encountered, and the need to capture fast-moving objects at night with high-enough contrast.
“Typically,” says Richard Goh, Founder of Optasia Systems (Tembeling, Singapore; http://www.optasia.com.sg), “low-cost image sensors are used in IP cameras, resulting in long exposure times and often blurred images. Such systems also tend to encompass standards such as H.264/5 encoding that uses a hybrid of motion-compensated inter-picture prediction and spatial transform coding using the discrete cosine transform (DCT). Because this technique is not lossless, it results in compression artifacts appearing in transmitted images which makes it more difficult to interpret the alphanumeric characters associated with license plates.”
Tomi Engdahl says:
Govt to support AI semiconductor development
http://the-japan-news.com/news/article/0004255286
Aiming to promote the development of semiconductors for artificial intelligence, the government will start providing assistance for start-ups and young researchers jointly with companies such as SoftBank Group Corp., Sony Corp. and Fujitsu Ltd., according to sources.
The government plans to hold its first “contest” to compete for new technologies in 2018 and provide outstanding companies and talents with development funds and other support, the sources said.
AI semiconductors will be key to developing new-generation technologies such as self-driving cars, and the government aims to develop AI semiconductors that will become global standards through public-private cooperation.
The aim of the contest is to find standout talent and the seeds of technologies necessary for developing advanced AI semiconductors, they said.
Tomi Engdahl says:
OpenAI Releases Algorithm That Helps Robots Learn from Hindsight
https://spectrum.ieee.org/automaton/robotics/artificial-intelligence/openai-releases-algorithm-that-helps-robots-learn-from-hindsight
Today, San Francisco-based AI research company OpenAI is releasing an open source algorithm called Hindsight Experience Replay, or HER, which reframes failures as successes in order to help robots learn more like humans.
Tomi Engdahl says:
AI Beats Dermatologists in Diagnosing Nail Fungus
https://spectrum.ieee.org/the-human-os/robotics/artificial-intelligence/ai-beats-dermatologists-in-diagnosing-nail-fungus
It’s still relatively rare for artificial intelligence to deliver a crushing victory over human physicians in a head-to-head test of medical expertise. But a deep neural network approach managed to beat 42 dermatology experts in diagnosing a common nail fungus that affects about 35 million Americans each year.
“This study was the first to show that AI has overwhelmed the specialists,” says Seung Seog Han, a dermatologist and clinician at I Dermatology in Seoul, South Korea. “Until now, in many studies, AI was similar to that of a specialist in diagnosis of diabetic retinopathy, diagnosis of skin cancer, and chest X-ray readings.”
Tomi Engdahl says:
The state of AI: 10 eye-opening statistics
https://enterprisersproject.com/article/2018/2/state-ai-10-eye-opening-statistics?sc_cid=7016000000127ECAAY
Analysts say 2018 will be the year AI plans become reality. Consider these recent stats and trends on artificial intelligence
Tomi Engdahl says:
Systems Bits: Feb. 27
AI alarm sounded; systems engineering inspiration; autonomous vehicle tradeoffs.
https://semiengineering.com/systems-bits-feb-27/
Prepare to prevent malicious AI use
According to the University of Cambridge, 26 experts on the security implications of emerging technologies have jointly authored a ground-breaking report thereby sounding the alarm about the potential malicious use of artificial intelligence (AI) by rogue states, criminals, and terrorists.
The report forecasts rapid growth in cyber-crime and the misuse of drones during the next decade as well as an unprecedented rise in the use of ‘bots’ to manipulate everything from elections to the news agenda and social media. This adds up to a clarion call for governments and corporations worldwide to address the clear and present danger inherent in the myriad applications of AI, they said.
The report – The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation – also insists on interventions to mitigate the threats posed by the malicious use of AI. Specifically, policy-makers and technical researchers need to work together now to understand and prepare for the malicious use of AI.
They acknowledge that AI has many positive applications, but it is a dual-use technology and AI researchers and engineers should be mindful of and proactive about the potential for its misuse.
The 100-page report identifies three security domains (digital, physical, and political security) as particularly relevant to the malicious use of AI. It suggests that AI will disrupt the trade-off between scale and efficiency and allow large-scale, finely targeted and highly efficient attacks.
Tomi Engdahl says:
Chaim Gartenberg / The Verge:
Google unveils Learn with Google AI site for AI and machine learning resources, posts free 15-hour Machine Learning Crash Course used by 18K Google employees — A new ‘Learn with Google AI’ site will serve as a hub for AI and machine learning resources — Machine learning and AI …
Google wants to teach more people AI and machine learning with a free online course
https://www.theverge.com/2018/2/28/17063780/google-ai-machine-learning-hub-crash-course-free
A new ‘Learn with Google AI’ site will serve as a hub for AI and machine learning resources
Tomi Engdahl says:
Clare McGrane / GeekWire:
Microsoft announces four new services aimed at healthcare professionals, including Microsoft Genomics for genetic analyses and AI-based Empower MD platform
Microsoft and UPMC unveil virtual AI assistant that listens in and takes notes on doctor’s visits
https://www.geekwire.com/2018/microsoft-healthcare/
Microsoft wants to use technology to make things easier and more efficient in those situations. The company announced a slew of new cloud- and artificial-intelligence-fueled technologies Wednesday as part of its Healthcare NExT program, all aimed at helping healthcare providers wage a technology revolution in the industry.
The company announced four new projects: A healthcare-focused Azure cloud blueprint; Microsoft Genomics, a platform that powers genetic analysis and personalized medicine; A new template for Microsoft Teams specialized for healthcare providers; and Empower MD: an artificial intelligence platform that can assist doctors by listening in and learning from their conversations with patients.
The AI scribe was developed by the University of Pittsburgh Medical Center (UPMC), in collaboration with Microsoft, as a proof of concept. The application analyzes a doctor’s conversation with a patient and then makes suggestions in the patient’s electronic health record.
Tomi Engdahl says:
Ali Winston / The Verge:
Sources: Palantir has been secretly testing predictive policing technology in New Orleans since 2012 that identifies individuals at risk of committing crime
Palantir has secretly been using New Orleans to test its predictive policing technology
https://www.theverge.com/2018/2/27/17054740/palantir-predictive-policing-tool-new-orleans-nopd
Palantir deployed a predictive policing system in New Orleans that even city council members don’t know about
The program began in 2012 as a partnership between New Orleans Police and Palantir Technologies, a data-mining firm founded with seed money from the CIA’s venture capital firm. According to interviews and documents obtained by The Verge, the initiative was essentially a predictive policing program, similar to the “heat list” in Chicago that purports to predict which people are likely drivers or victims of violence.
The partnership has been extended three times, with the third extension scheduled to expire on February 21st, 2018. The city of New Orleans and Palantir have not responded to questions about the program’s current status.
Predictive policing technology has proven highly controversial wherever it is implemented
More than half a decade after the partnership with New Orleans began, Palantir has patented at least one crime-forecasting system and has sold similar software to foreign intelligence services for predicting the likelihood of individuals to commit terrorism.
Tomi Engdahl says:
Feeding Frenzy for AI Engineers Gets More Intense
https://spectrum.ieee.org/view-from-the-valley/at-work/tech-careers/feeding-frenzy-for-ai-engineers-gets-more-intense
In December, Bloomberg reported that desperate demand for software engineers who know how to build artificial intelligence systems turned a previously low-key academic event “into a recruiting frenzy more akin to the National Football League’s draft day.”
Meanwhile, the Tencent Research Institute released a report indicating that there are currently only 300,000 AI researchers and practitioners worldwide, but the demand is for millions.
Tomi Engdahl says:
Microsoft advances several of its hosted artificial intelligence algorithms
https://techcrunch.com/2018/03/01/microsoft-advances-several-of-its-hosted-artificial-intelligence-algorithms/?utm_source=tcfbpage&sr_share=facebook
Tomi Engdahl says:
ScopeAI helps companies analyze their customer feedback
https://techcrunch.com/2018/03/01/scopeai-seed-funding/?utm_source=tcfbpage&sr_share=facebook
If you’re running a company with a lot of customers, it can take time to sort through all that feedback. A startup called ScopeAI is working to make that process a lot easier.
Tomi Engdahl says:
Ceva Uses Machine Learning to Bolster Wireless Modems
http://www.mwrf.com/semiconductors/ceva-uses-machine-learning-bolster-wireless-modems
To increase the throughput of wireless networks, companies are expanding into higher spectrum bands than ever before to connect everything from smartphones to cars to the internet. The problem is that these millimeter waves can be blocked by buildings and trees and absorbed by oxygen over long distances.
The solution is to use beamforming to steer antenna beams around obstacles. The technology measures channel state information like phase and gain in specific slices of spectrum. But instead of using traditional software to adapt transmissions to the channel conditions, several companies are looking into machine learning.
Among them is Ceva, a chip designer that licenses digital signal processors that convert everything from voices to wireless signals into digital data. The company recently said that it had designed a custom accelerator that can be embedded in 5G modems to enable advanced beamforming and link adaptation.
The custom processor is one of the building blocks of the company’s new PentaG platform.
Tomi Engdahl says:
Artificial intelligence and machine learning capabilities for industrial robots
http://www.controleng.com/single-article/artificial-intelligence-and-machine-learning-capabilities-for-industrial-robots/235dbae71e420771f91fe37228c2bb7b.html
Artificial intelligence (AI) and machine learning capabilities are making their way into industrial robotics technology as manufacturers look to make robots smarter and more collaborative in their day-to-day activities on the plant floor.
Artificial intelligence (AI) and machine learning capabilities are making their way into industrial robotics technology as manufacturers look to improve on the rigid, inflexible capabilities of standard industrial robots.
The merging of robotics and AI technology has several consequences. Early adopters of these new robotic systems are reaping the benefits. The technology, while relatively new, is widely available and impacts manufacturing processes in a number of ways.
Tomi Engdahl says:
ST Projects Embedded AI Vision
https://www.eetimes.com/document.asp?doc_id=1333015
As expected, AI is the crowd magnet at this year’s Mobile World Congress. As Jem Davies, vice president, fellow and general manager of the machine learning group at Arm, quipped, during an interview with EE Times, “Machine learning is a bit like fleas. Everyone has got one.”
Companies who already tipped their plans for machine learning prior to the show include Arm pushing its Project Trillium, MediaTek for P60, Ceva with PentaG and startup GreenWaves’ GAP8.
STMicroelectronics, meanwhile, broke its silence and discussed during the company’s press conference Tuesday (Feb. 27) how the company sees machine learning as a key to “distributed intelligence” in the embedded world. ST envisions a day when a network of tiny MCUs become smart enough to detect wear and tear in machines on the factory floor or find anomalies in a building, without reporting sensory data every so often back to data centers.
Tomi Engdahl says:
AI will create new jobs but skills must shift, say tech giants
https://techcrunch.com/2018/02/28/ai-will-create-new-jobs-but-skills-must-shift-say-tech-giants/
AI will create more jobs than it destroys was the not-so-subtle rebuttal from tech giants to growing concern over the impact of automation technologies on employment. Execs from Google, IBM and Salesforce were questioned about the wider societal implications of their technologies during a panel session here at Mobile World Congress.
Behshad Behzadi, who leads the engineering teams working on Google’s eponymously named AI voice assistant, claimed many jobs will be “complemented” by AI, with AI technologies making it “easier” for humans to carry out tasks.
“For sure there is some shift in the jobs. There’s lots of jobs which will [be created which don’t exist today]. Think about flight attendant jobs before there was planes and commercial flights. No one could really predict that this job will appear. So there are jobs which will be appearing of that type that are related to the AI,” he said.
“I think the topic is a super important topic. How jobs and AI is related — I don’t think it’s one company or one country which can solve it alone. It’s all together we could think about this topic,” he added. “But it’s really an opportunity, it’s not a threat.”
Tomi Engdahl says:
AI Comes to Sensing Devices
https://www.eetimes.com/document.asp?doc_id=1333003
GreenWaves Technologies, a startup based in Grenoble, France, launched an apps processor designed to do image, sound and vibration AI analysis on battery-operated sensing devices. The processor, called GAP8, is built on the RISC-V and PULP open-source projects.
Greenwaves’ first sample chip just came back last week from TSMC, which built it using its 55nm low power process. With this brainchild in hand, the company is pitching its GAP8 processor and GAP8 software development kit this week both at Mobile World Congress here and Embedded World in Nürnberg, Germany.
Mike Demler, senior analyst at the Linley Group, told us, “It’s the first time I’ve seen someone add a neural engine to an MCU-class processor.”
Tomi Engdahl says:
Building AI systems that work is still hard
https://techcrunch.com/2018/01/01/building-ai-systems-that-work-is-still-hard/?utm_source=tcfbpage&sr_share=facebook
Even with the support of AI frameworks like TensorFlow or OpenAI, artificial intelligence still requires deep knowledge and understanding compared to a mainstream web developer. If you have built a working prototype, you are probably the smartest guy in the room. Congratulations, you are a member of a very exclusive club.
With Kaggle, you can even earn decent money by solving real-world projects.
Tomi Engdahl says:
Nathan Vanderklippe / Globe and Mail:
Human Rights Watch: China’s Xinjiang region uses big data on everyday habits and AI for predictive policing to send people to political re-education camps
China using big data to detain people before crime is committed: report
https://www.theglobeandmail.com/news/world/china-using-big-data-to-detain-people-in-re-education-before-crime-committed-report/article38126551/
Barely seven months ago, a senior Chinese official promised that artificial intelligence could one day help authorities spot crime before it happens.
In the country’s far western Xinjiang region, it’s already happening, with the establishment of a system that critics call “Orwellian” in scope and ambition, and which is being used to place people in political re-education.
Called the Integrated Joint Operations Platform, or IJOP, it assembles and parses data from facial-recognition cameras, WiFi internet sniffers, licence-plate cameras, police checkpoints, banking records and police reports made on mobile apps from home visits, a new report from Human Rights Watch finds.
If the system flags anything suspicious – a large purchase of fertilizer, perhaps, or stockpiles of food considered a marker of terrorism – it notifies police, who are expected to respond the same day and act according to what they find. “Who ought to be taken, should be taken,” says a work report located by the rights organization.
Another official report shows how reports generated by IJOP are used to send people to an “Occupational Skills and Education Training Centre” where political re-education is carried out.
Tomi Engdahl says:
Devin Coldewey / TechCrunch:
Google AI can now easily replace the video background in YouTube stories on mobile, available in beta to a limited number of YouTube creators
Google’s new YouTube Stories feature lets you swap out your background (no green screen required)
https://techcrunch.com/2018/03/01/googles-new-youtube-stories-feature-lets-you-swap-out-your-background-no-green-screen-required/
Google researchers know how much people like to trick others into thinking they’re on the moon, or that it’s night instead of day, and other fun shenanigans only possible if you happen to be in a movie studio in front of a green screen. So they did what any good 2018 coder would do: build a neural network that lets you do it.
This “video segmentation” tool, as they call it (well, everyone does) is rolling out to YouTube Stories on mobile in a limited fashion starting now — if you see the option, congratulations, you’re a beta tester.
A lot of ingenuity seems to have gone into this feature.
On mobile, though, and with an ordinary RGB image, it’s not so easy to do. And if doing a still image is hard, video is even more so, since the computer has to do the calculation 30 times a second at a minimum.
Well, Google’s engineers took that as a challenge, and set up a convolutional neural network architecture, training it on thousands of labelled images like the one to the right.
The result is a fast, relatively accurate segmentation engine that runs more than fast enough to be used in video — 40 frames per second on the Pixel 2 and over 100 on the iPhone 7 (!).
Tomi Engdahl says:
Frank Hersey / TechNode:
76.3% of Chinese respondents believe AI is a threat to privacy in an 8,000 person survey carried out by state-run TV network CCTV and Tencent Research
Almost 80% of Chinese concerned about AI threat to privacy, 32% already feel a threat to their work
http://technode.com/2018/03/02/almost-80-chinese-concerned-ai-threat-privacy-32-already-feel-threat-work/
AI is a threat to privacy—this is how 76.3% of Chinese people feel about artificial intelligence technology according to a survey of 8,000 participants carried out by CCTV and Tencent Research. Facial recognition was the usage of AI for which respondents had the highest awareness, and over half felt AI was already having an impact on their work and life.
The survey also revealed a high awareness of AI among the population.
Tomi Engdahl says:
Intel senior executive impressed about Chinese AI research, development
http://www.xinhuanet.com/english/2018-03/04/c_137015880.htm
SAN FRANCISCO, March 4 (Xinhua) — Intel Vice President of Strategy Innovation and Planning of Programmable Solutions Group Vincent Hu said Saturday that he is very much impressed about artificial intelligence (AI) research in China in recent years.
China was investing heavily in AI, and the United States and China were probably the two leading countries in such research, Hu told Xinhua in an interview during the 2018 Spring Symposium on AI and semiconductor fusion, sponsored by Chinese American Semiconductor Professional Association (CASPA) in Cupertino, south of San Francisco in the U.S. state of California.
“I think one of the assets that China has is a very strong university program. And that is where most of the research in AI and machine learning is occurring today, which has been led by universities, just like in the United States,” he said.
Citing the research in quantum computing right now in China, he said, “I think that’s where I’ve been impressed about what the Chinese universities are doing out there.”
China has many very creative and imaginative people, and Intel always hires talents from many countries
Tomi Engdahl says:
Arm GPU Gets More AI Muscle
Mali G52 claims 3.6x boost for neural nets
https://www.eetimes.com/document.asp?doc_id=1333030
ARM announced four new cores for mainstream smartphones and digital TVs, two Mali GPUs and associated video and display cores for them. The news shows that Arm is, at least for now, taking a three-tier approach to machine learning and that China mobile OEMs are becoming increasingly influential.
Arm’s new Mali G52 GPU core is aimed at mid-tier smartphones and digital TVs using combinations of Cortex-A72 and -A55 CPU cores. The GPU boosts machine-learning performance up to 3.6x for ImageNet classifiers compared to its existing G51 core.
Tomi Engdahl says:
AI Attempts To Write Goop-Style Website And It’s Both Ludicrous And Scarily Convincing
http://www.iflscience.com/health-and-medicine/ai-attempts-to-write-goopstyle-website-and-its-both-ludicrous-and-scarily-convincing/
Goop, if you’re not already aware, is the “lifestyle brand” owned and promoted by Gwyneth Paltrow. For background, it won the worst pseudoscience of the year award
Goop usually shows up in the news every now and then after launching some new unscientific nonsense
Botnik Studios is a team that takes words from real websites, scripts, and other texts and then uses them as bases for new predictive text keyboards. They have turned their attention to Goop and created a parody website, and it’s brilliant.
They fed text from Goop’s website into their app, made a predictive text keyboard using the (bizarre) input, and out came Goob.
http://botnik.org/content/goob.html
Tomi Engdahl says:
Arm GPU Gets More AI Muscle
Mali G52 claims 3.6x boost for neural nets
https://www.eetimes.com/document.asp?doc_id=1333030
ARM announced four new cores for mainstream smartphones and digital TVs, two Mali GPUs and associated video and display cores for them. The news shows that Arm is, at least for now, taking a three-tier approach to machine learning and that China mobile OEMs are becoming increasingly influential.
Arm’s new Mali G52 GPU core is aimed at mid-tier smartphones and digital TVs using combinations of Cortex-A72 and -A55 CPU cores. The GPU boosts machine-learning performance up to 3.6x for ImageNet classifiers compared to its existing G51 core.
The G52 packs eight execution engines compared to four on the G51, with four lanes in each engine and each capable of up to four 8-bit integer multiply-accumulate operations per cycle. Up to four G52s can be used in an SoC, each executing up to 288 MACs/cycle.
Tomi Engdahl says:
Finland wants to get rid of routine programming – an artificial intelligence aid
Artificial intelligence would increase the software’s intelligence, efficiency and modularity, which at least partially would offset the labor shortage of existing thousands of programmers. Innovation developed at Aalto University would facilitate development especially in large IT projects.
Extensive information systems are currently being built by modifying and combining old systems. Now, the new innovation that is being developed at Aalto University will lower the development costs so that systems such as Apot can be started on a clean sheet.
Business Finland has contributed 678,000 euros to Aalto University researcher Jussi Rintanen’s new artificial intelligence information system innovation. Rintanen wants not only to automate the development of information systems, but also to integrate all parts of the system into a single functional entity.
At Aalto University, innovation is being developed to reduce the development costs of large-scale IT systems so that systems like the Apot used in health care can be started on a clean sheet. The invention is based on the use of artificial intelligence.
Information systems projects in the health care and state administration are very much tied to the workforce. The information system market in Finland is approximately EUR 2 billion annually, globally estimated at EUR 200 billion.
Expensive, long-term or incomplete information system projects often have the same basic problem: a huge amount of routine programming work that is difficult to manage. Building up complete systems from the very beginning in modern programming language would be extremely laborious. Therefore, it is often decided to extend and modify old systems even if they do not meet the needs of organizations or users.
- Large information systems are often based on the ancient program code and the old-fashioned programming language. For example, Apuoli’s social and health care system is built with an old program code based on the MUMPS programming language developed in the 1960s, “says Rintanen.
Innovation developed by the Rintane team will especially automate such large projects. Thanks to this, conventional manual programming is reduced and greatly simplified. The cost of development is so low that information systems can be designed from the beginning to meet customer needs.
The technology designed by Rintanen’s colleagues is based on the automation of reasoning. In the usual program development, the programmer’s attention is in the details of the program code, when in the new technology the programs are generated by automatic search methods and logical reasoning. In the future, technology will be further expanded by automatic decision-making, making information systems more intelligent.
- The aim is to make software more flexible and to better understand the world’s activities outside the information system and the basics of decision-making. For example, in health care, more intelligent information systems could take on much more responsibility for administrative tasks and decision-making.
Experimenting business and business models will also be easier when software making becomes more affordable and easier. For example, the creation and design of websites and stores are cheaper and can be easily made more complex.
Sources:
https://www.uusiteknologia.fi/2018/03/06/suomi-haluaa-eroon-rutiiniohjelmoinnista-tekoaly-apuun/
http://etn.fi/index.php?option=com_content&view=article&id=7662&via=n&datum=2018-03-06_14:53:56&mottagare=30929
Tomi Engdahl says:
Windows 10’s next major update will include Windows ML, a new AI platform
https://www.theverge.com/2018/3/7/17089860/microsoft-windows-ml-windows-10-ai-platform
Microsoft is planning to include more artificial intelligence capabilities inside Windows 10 soon. The software giant is unveiling a new AI platform, Windows ML, for developers today, that will be available in the next major Windows 10 update available this spring. Microsoft’s new platform will enable all developers that create apps on Windows 10 to leverage existing pre-trained machine learning models in apps.
Windows ML will enable developers to create more powerful apps for consumers running Windows 10. Developers will be able to import existing learning models from different AI platforms and run them locally on PCs and devices running Windows 10, speeding up real-time analysis of local data like images or video, or even improving background tasks like indexing files for quick search inside apps. Microsoft has already been using AI throughout Office 365, inside the Windows 10 Photos app, and even with its Windows Hello facial recognition to allow Windows 10 users to sign into PCs and laptops with their faces.
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/7672-winml-tekoaly-tulee-windowsiin
Tomi Engdahl says:
With Windows ML, Intel AI to Invade Mobile PCs
https://www.eetimes.com/document.asp?doc_id=1333045
It might not be too long before your average mobile PC will feature — on its motherboard — not just CPUs and GPUs but also an embedded AI inference chip, like the Intel/Movidius Vision Processor Unit (VPU).
The first clue for this scenario unfolded in Microsoft Corp.’s launch announcement today, at its Windows Developer Day, of Windows ML, an open-standard framework for machine-learning tasks in the Windows OS. Microsoft said that it is extending Windows OS native support for the Intel/Movidius VPU. Implied in the message is that Intel/Movidius has taken a step closer to finding a home not just in embedded applications, such as drones and surveillance cameras, but also in Windows-based laptops and tablets.
In a telephone interview with EE Times, Gary Brown, director of marketing at Movidius/Intel, confirmed, “Although today’s announcement isn’t about that [VPU integration on a mobile PC], yes, you will see VPU migrating into a PC motherboard.”
Tomi Engdahl says:
Yes, Alexa is all very well…but we want YOU to talk machine learning and AI
MCubed call for papers open now
https://www.theregister.co.uk/2018/03/08/yes_alexa_is_all_very_wellbut_we_want_you_to_talk_machine_learning_and_ai/
Tomi Engdahl says:
People face the threats of artificial intelligence like lung cancer: “Do not hit the spot”
In the recent Yankee survey, the answers were affected by how long a person had been studying. Those who received less than four years of college-level education were more concerned (28%) than those who had completed at least a bachelor’s degree (15%).
Almost three out of four Americans (73 percent) estimate that artificial intelligence will eliminate more jobs than what it creates.
At the same time, less than a quarter (23%) said they were worried or very concerned about the effects of automation on the respondent’s own job
Source: https://summa.almatalent.fi/article/tv/uutiset/ihmiset-suhtautuvat-tekoalyn-uhkiin-kuin-keuhkosyopaan-ei-osu-kohdalle/429703
Tomi Engdahl says:
Next Big Windows Update Will Bring Hardware-Accelerated AI
https://slashdot.org/story/18/03/07/1957209/next-big-windows-update-will-bring-hardware-accelerated-ai?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+Slashdot%2Fslashdot%2Fto+%28%28Title%29Slashdot+%28rdf%29%29
Tomi Engdahl says:
The Defense Department is taking on ISIS with Google’s open-source AI software
https://www.technologyreview.com/the-download/610429/the-defense-department-is-taking-on-isis-with-googles-open-source-ai-software/
The search giant’s AI will be helping to analyze drone footage. Not everyone at the “don’t be evil” company is pleased.
War games: Google is giving the US Department of Defense special access to TensorFlow, the company’s machine-learning software library, to help analyze images from drones. Gizmodo reports that some Google employees are not happy about providing their technology for military uses.
Tomi Engdahl says:
Wave Computing Chooses MIPS 64-bit RISC
https://www.eetimes.com/document.asp?doc_id=1333046
MIPS, a storied but beleagured RISC processor core company, is coming back to life. Breathing new life into MIPS are a new customer — Wave Computing — and a number of existing clients that include Intel/Mobileye, NetSpeed, Fungible, ThiCI and Denso. All have pledged to use MIPS 64-bit multi-threaded processor core to handle device management and control functions inside their respective AI processors — many either in development or ready for rollout.
Wave Computing is a designer of a massively parallel dataflow architecture called Wave Dataflow Processing Unit (DPU) for deep learning. Wave Computing, which is getting ready to roll out its beta system in the next few weeks by using the company’s first-generation processor, has decided to use MIPS 64-bit CPU for the company’s second-generation DPU, Derek Meyer, Wave Computing CEO and a veteran of MIPS, told EE Times.
Tomi Engdahl says:
AI Core – Artificial Intelligence On The Edge
https://www.eeweb.com/profile/eeweb/news/ai-core-artificial-intelligence-on-the-edge
UP Bridge the Gap – a brand of AAEON Europe – is proud to launch AI Core: the first embedded ultra-compact Artificial Intelligence processing cards for edge computing.
AI Core is a mini-PCIe module powered by Intel® Movidius™ Myriad™ 2 technology. This low-power module enhances industrial IoT edge devices with hardware accelerated deep learning and enhanced machine vision functionality. AAEON Technology is one of the first IPC manufacturers to address the growing need for Artificial Intelligence on the edge with dedicated hardware.
Most of the available IoT solutions are focused on connecting edge devices to the cloud and these deployments face challenges related to latency, network bandwidth, reliability and security. Experts in this field agree that not all the tasks and decision making processes can be addressed in cloud-only models. AI Core is the solution for cloud limitations by bringing AI performance and hardware acceleration not “at” but “ON” the edge of the Internet of Things.
Tomi Engdahl says:
How AI Impacts Memory Systems
https://semiengineering.com/how-ai-impacts-memory-systems/
The ways different architectures get around the memory bottleneck.