3 AI misconceptions IT leaders must dispel

https://enterprisersproject.com/article/2017/12/3-ai-misconceptions-it-leaders-must-dispel?sc_cid=7016000000127ECAAY

 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,”

5,117 Comments

  1. Tomi Engdahl says:

    Ingrid Lunden / TechCrunch:
    China-based Geek+, which makes AI robots like unmanned forklifts to pick, move, and sort things in warehouses, raises $150M Series B led by Warburg Pincus

    China’s Geek+ raises $150M to build robots for warehouses and logistics
    https://techcrunch.com/2018/11/22/chinas-geek-raises-150m-to-build-robots-for-warehouses-and-logistics/

    Reply
  2. Tomi Engdahl says:

    Drew Harwell / Washington Post:
    How Predictim uses AI to generate a score of babysitters’ character by analyzing years of online activity and provides questionable recommendations to parents — When Jessie Battaglia started looking for a new babysitter for her 1-year-old son, she wanted more information …
    http://www.washingtonpost.com/technology/2018/11/16/wanted-perfect-babysitter-must-pass-ai-scan-respect-attitude/

    Reply
  3. Tomi Engdahl says:

    THE DIY TINKERERS HARNESSING THE POWER OF ARTIFICIAL INTELLIGENCE
    https://www.wired.com/story/diy-tinkerers-artificial-intelligence-smart-tech/

    People like Ng have big hopes for the amateur AI explosion: They want it to spread the technology’s potential far from Silicon Valley, physically and culturally, to see what happens when tech outsiders “train” neural networks according to their own priorities and ways of seeing the world. Ng likes to imagine that one day a person in India might use what they learn in online videos about AI to make their local water safer to drink.

    Of course, not every DIY neural network will be quite so G-rated.

    The poster explained that the clip was fake, created by training a neural network to generate images of Gadot’s face that matched the expressions of the video’s original star. They then released the code and methodology online so anyone could make similar “deepfake” clips of their own.

    So the age of homebrew AI may not be all sweetness and light. Nor will it be all darkness and porn.

    Reply
  4. Tomi Engdahl says:

    The Story of Lenny, the Internet’s Favorite Telemarketing Troll
    https://motherboard.vice.com/en_us/article/d3b7na/the-story-of-lenny-the-internets-favorite-telemarketing-troll

    Lenny is a decade-old chatbot designed to troll telemarketers that has developed a cult following online. It’s remarkably convincing, but is it actually effective?

    Reply
  5. Tomi Engdahl says:

    Japan Sniffing Out Its AI Niches
    https://www.eetimes.com/document.asp?doc_id=1334011

    As with any trade show featuring “embedded technology” anywhere in the world, the Embedded Technology 2018 Exhibition in Yokohama earlier this month got hijacked by today’s two hot topics: AI and IoT.

    On one hand, Japanese electronics heavyweights — mostly Fujitsu, NEC and Toshiba — showcased new materials and wireless technologies they deem critical to the spread of IoT applications.

    On the other hand, this year’s Embedded Technology/IoT show trotted out a host of Japanese startups, including Ascent Robotics, LeapMind, Robit and others with an intense business and technology focus on AI.

    Japanese startups tend to differ from startups elsewhere in their commitment to leverage Japan’s decades of experience in building robots and automobiles. They want to use their proximity to automated manufacturing sites and to experienced factory managers as a head start toward developing AI algorithms for industrial applications.

    While Google, Facebook, Amazon and others in the United States may have already established a stronghold in areas like big data, data centers and deep learning, Japan’s hopes focus on making edge devices smarter, more connected and autonomous.

    Reply
  6. Tomi Engdahl says:

    Separating AI Hype From Reality
    https://www.eetimes.com/author.asp?section_id=240&doc_id=1334002

    Artificial intelligence (AI) is what the Internet of Things was two years ago – overhyped and not very well understood.

    Kurt Sievers, president of NXP Semiconductors, said at a CEO roundtable at electronica in Munich that AI is overhyped today . “It’s this miraculous thing where nobody knows what it is,” he said. “Most people wouldn’t even know what the definition is.”

    Reply
  7. Tomi Engdahl says:

    Imec, CEA-Leti Form AI and Quantum Computing Hub
    https://www.eetimes.com/document.asp?doc_id=1334000

    Two of Europe’s key electronics and nanotechnologies research institutes — imec in Belgium and CEA-Leti in France — will collaborate to develop a European hub for artificial intelligence and quantum computing.

    As security and privacy issues rise up the agenda in almost every organization, the race is on to process more at the edge and put more intelligence at endpoints. For electronics systems design, most of the major chip companies now offer or are developing deep learning and edge AI devices or intellectual property. The edge AI devices are often complete computer sub-systems displaying intelligent behavior locally on the hardware devices (chips), analyzing their environment and taking required actions to achieve specific goals.

    Reply
  8. Tomi Engdahl says:

    New Boom in Facial Recognition Tech Prompts Privacy Alarms
    https://threatpost.com/new-boom-in-facial-recognition-tech-prompts-privacy-alarms/138979/

    Tech advances are accelerating the use of facial recognition as a reliable and ubiquitous mass surveillance tool, privacy advocates warn.

    Somewhat quietly over the past couple of years there has been a flurry of breakthroughs in biometric technology, led by some leapfrog advances in facial recognition systems.

    Now facial recognition appears to be on the verge of blossoming commercially, with security use-cases paving the way.

    Reply
  9. Tomi Engdahl says:

    British Cops Are Building an AI That Flags People for Crimes That Haven’t Happened Yet
    https://gizmodo.com/british-cops-are-building-an-ai-that-flags-people-for-c-1830680569

    Police in the UK are piloting a project that uses artificial intelligence to determine how likely someone is to commit or be a victim of a serious crime.

    Filed to: MINORITY REPORT

    Reply
  10. Tomi Engdahl says:

    Ashley Carman / The Verge:
    Instagram begins rolling out a tool that describes photos for visually impaired users using AI or user descriptions

    Instagram is now using AI to describe photos for users with visual impairments
    They’ll know what they’re seeing
    https://www.theverge.com/2018/11/28/18116323/instagram-ai-visual-impairment-description

    Reply
  11. Tomi Engdahl says:

    Obfuscated Command Line Detection Using Machine Learning
    https://www.fireeye.com/blog/threat-research/2018/11/obfuscated-command-line-detection-using-machine-learning.html

    This blog post presents a machine learning (ML) approach to solving an emerging security problem: detecting obfuscated Windows command line invocations on endpoints. We start out with an introduction to this relatively new threat capability, and then discuss how such problems have traditionally been handled. We then describe a machine learning approach to solving this problem and point out how ML vastly simplifies development and maintenance of a robust obfuscation detector. Finally, we present the results obtained using two different ML techniques and compare the benefits of each.

    Reply
  12. Tomi Engdahl says:

    A Breakthrough in FPGA-Based Deep Learning Inference
    https://www.eeweb.com/profile/lauro/articles/a-breakthrough-in-fpga-based-deep-learning-inference

    Mipsology’s Zebra Deep Learning inference engine is designed to be fast, painless, and adaptable, outclassing CPU, GPU, and ASIC competitors.

    I recently attended the 2018 Xilinx Development Forum (XDF) in Silicon Valley. While at this forum, I was introduced to a company called Mipsology, a startup in the field of artificial intelligence (AI) that claims to have solved the AI-related problems associated with field-programmable gate arrays (FPGAs). Mipsology was founded with a grand vision to accelerate the computation of any neural network (NN) with the highest performance achievable on FPGAs without the constraints inherent in their deployment.

    Reply
  13. Tomi Engdahl says:

    AI a Focus as U.S. Preps Export Controls
    U.S. outlines 14 broad areas in effort aimed mainly at China
    https://www.eetimes.com/document.asp?doc_id=1334020

    Uncle Sam wants to restrict a few good technologies — and it needs engineers to help identify them.

    As part of legislation passed this summer, the U.S. Commerce Department put out a call for input by December 19 on which of 14 broad emerging technologies should face export controls. The call quickly got attention from industry veterans and groups concerned controls could hurt U.S. companies and worsen a growing tech trade war with China.

    Reply
  14. Tomi Engdahl says:

    http://www.etn.fi/index.php/13-news/8776-samsung-lisasi-tekoalyn-kannykkapiirilleen

    Applen ja Huawein puhelimien uudet tekoälyominaisuudet ovat ihastuttaneet monia käyttäjiä. Nyt suurin valmistaja Samsung vastaa haasteeseen uusimmalla Exynos-sarjan sovellusprosessorillaan

    Samsungin mukaan Exynos 9820-piiri suoriutuu tekoälylaskennasta uuden NPU-yksikön voimalla jopa seitsemän kertaa edeltäjäänsä nopeammin. Tämä tarkoittaa esimerkiksi selvästi nopeampaa kuvan tunnistusta tai kameran asetusten muokkaamista ympäristön mukaan.

    Reply
  15. Tomi Engdahl says:

    AWS announces new Inferentia machine learning chip
    https://techcrunch.com/2018/11/28/aws-announces-new-inferentia-machine-learning-chip/

    “Inferentia will be a very high-throughput, low-latency, sustained-performance very cost-effective processor,” AWS CEO Andy Jassy explained during the announcement.

    Reply
  16. Tomi Engdahl says:

    Amazon Elastic Inference will reduce deep learning costs by ~75%
    https://techcrunch.com/2018/11/28/amazon-elastic-inference-will-reduce-deep-learning-costs-by-75/

    “What we see typically is that the average utilization of these P3 instances GPUs are about 10 to 30 percent, which is pretty wasteful with elastic inference. You don’t have to waste all that costs and all that GPU,” AWS chief executive Andy Jassy said onstage at the AWS re:Invent conference earlier today. “[Amazon Elastic Inference] is a pretty significant game changer in being able to run inference much more cost-effectively.”

    Reply
  17. Tomi Engdahl says:

    Amazon launches an automated labeling service for its SageMaker machine learning tool
    https://techcrunch.com/2018/11/28/amazon-launches-an-automated-labeling-service-for-its-sagemaker-machine-learning-tool/

    You can’t build a good machine learning model without good training data. But building those training sets is hard, often manual work, that involves labeling thousand and thousands of images, for example. With SageMaker, AWS has been working on a service that makes building machine learning models a lot easier. But until today, that labeling task was still up to the user. Now, however, the company is launching SageMaker Ground Truth, a training set labeling service.

    Reply
  18. Tomi Engdahl says:

    Amazon debuts new self-driving racing league with tiny machine learning-powered race cars
    https://www.geekwire.com/2018/amazon-debuts-new-autonomous-racing-league-tiny-machine-learning-powered-race-cars/

    We are pleased and excited to announce AWS DeepRacer and the AWS DeepRacer League. New reinforcement learning powered AWS service and racing league ML powered cars. #reInvent pic.twitter.com/9Qmmqj4Ebw

    — AWS re:Invent (@AWSreInvent) November 28, 2018

    Reply
  19. Tomi Engdahl says:

    AI Chip Architectures Race To The Edge
    https://semiengineering.com/ai-chip-architectures-race-to-the-edge/

    Companies battle it out to get artificial intelligence to the edge using various chip architectures as their weapons of choice.

    Reply
  20. Tomi Engdahl says:

    Why Is the US Losing the AI Race?
    https://www.designnews.com/electronics-test/why-us-losing-ai-race/123098124759857?ADTRK=UBM&elq_mid=6636&elq_cid=876648

    Why is the US, once an assumed leader in artificial intelligence, losing its foothold on the technology? And how can it get its position back?

    Two years ago, the emergence of autonomous driving technologies led Intel CEO Brian Krzanich to declare that data is the new oil. If that’s true, then artificial intelligence is the new oil refinery.

    AI is rapidly becoming a globally valued commodity. And nations that lead in AI will likely be the ones that guide the global economy in the near future.

    Reply
  21. Tomi Engdahl says:

    AWS DeepRacer – Go Hands-On with Reinforcement Learning at re:Invent
    https://aws.amazon.com/blogs/aws/aws-deepracer-go-hands-on-with-reinforcement-learning-at-reinvent/

    Reinforcement Learning is a type of machine learning that works when an “agent” is allowed to act on a trial-and-error basis within an interactive environment, using feedback from those actions to learn over time in order to reach a predetermined goal or to maximize some type of score or reward. This stands in contrast to other forms of machine learning such as Supervised Learning, where a set of facts (ground truths) are used to train a model so that it can make inferences.

    AWS DeepRacer
    Let’s talk about the hardware and software first. AWS DeepRacer is a 1/18th scale radio-controlled, four-wheel drive car

    There’s an Intel Atom® processor onboard, a 4 megapixel camera with 1080p resolution, fast (802.11ac) WiFi, multiple USB ports, and enough battery power to last for about 2 hours. The Atom processor runs Ubuntu 16.04 LTS, ROS (Robot Operating System), and the Intel OpenVino™ computer vision toolkit.

    Reply
  22. Tomi Engdahl says:

    Amazon opens up its internal machine learning training to everyone
    More than 30 courses are available for free.
    https://www.engadget.com/2018/11/26/amazon-opens-internal-machine-learning-training/

    Reply
  23. Tomi Engdahl says:

    British Cops Are Building an AI That Flags People for Crimes That Haven’t Happened Yet

    https://gizmodo.com/british-cops-are-building-an-ai-that-flags-people-for-c-1830680569?utm_medium=sharefromsite&utm_source=gizmodo_facebook&utm_campaign=sharebar&fbclid=IwAR0PtCp1ifIs12E8HS_-_MwbNIg-cnMtYioDXW_p97rg2Gs2ERu1E7MzGhM

    Police in the UK are piloting a project that uses artificial intelligence to determine how likely someone is to commit or be a victim of a serious crime.

    Reply
  24. Tomi Engdahl says:

    Inside the world of AI that forges beautiful art and terrifying deepfakes
    https://www.technologyreview.com/s/612501/inside-the-world-of-ai-that-forges-beautiful-art-and-terrifying-deepfakes/?utm_medium=tr_social&utm_source=facebook&utm_campaign=site_visitor.unpaid.engagement

    Generative adversarial networks, or GANs, are fueling creativity—and controversy. Here’s how they work.

    Reply
  25. Tomi Engdahl says:

    Intelligent Connectivity: the Fusion of 5G, AI and IoT
    https://www.gsma.com/iot/news/intelligent-connectivity-5g-ai-iot/

    Intelligent connectivity is the combination of high-speed, low-latency 5G networks, cutting-edge artificial intelligence (AI) and the linking of billions of devices through the Internet of Things (IoT). As these three revolutionary technologies combine they will enable transformational new capabilities in transport, entertainment, industry and public services, and much more beyond.

    https://www.gsma.com/IC/report/

    Reply
  26. Tomi Engdahl says:

    AI Gets $100M Bid from Qualcomm
    https://www.eetimes.com/document.asp?doc_id=1334027

    Qualcomm launched a $100 million venture fund at an event here where the level of enthusiasm for machine learning ran high. China’s SenseTime alone talked about taking in $3 billion for its platform, and others gave examples of AI quadrupling productivity and saving lives.

    The combination of 5G and AI is central to Qualcomm’s corporate strategy in the wake of its failed merger with NXP and slowing smartphone growth. The combination of the two technologies will expand the company’s addressable market to a smart internet of things, said chief executive Steve Mollenkopf.

    “The funnel of companies we talk to has widened” to include industrial, automotive, and health-care companies, among others, he said.

    Reply
  27. Tomi Engdahl says:

    IBM Guns for 8-bit AI Breakthroughs
    https://www.eetimes.com/document.asp?doc_id=1334029

    IBM researchers, for example, are detailing new AI approaches for both digital and analog AI chips. IBM boasts that its digital AI chip demonstrates, “for the first time, the successful training of deep neural networks (DNNs) using 8-bit floating point numbers while fully maintaining the accuracy on a spectrum of deep learning models and datasets.”

    He added, “All those broader questions require a much larger neural net, much larger data sets and multi-modal data sets coming in… [for that], we need changes in architecture and hardware to make all that happen.”

    Reply
  28. Tomi Engdahl says:

    DeepMind claims early progress in AI-based predictive protein modelling
    https://techcrunch.com/2018/12/03/deepmind-claims-early-progress-in-ai-based-predictive-protein-modelling/?sr_share=facebook&utm_source=tcfbpage

    Google -owned AI specialist, DeepMind, has claimed a “significant milestone” in being able to demonstrate the usefulness of artificial intelligence to help with the complex task of predicting 3D structures of proteins based solely on their genetic sequence.

    Reply
  29. Tomi Engdahl says:

    Ryan Smith / AnandTech:
    Nvidia announces a new $2,499 GPU called Titan RTX with 576 tensor cores, 24GB of GDDR6 memory, and the new Turing architecture, shipping later this month

    NVIDIA Unveils “Titan RTX” Video Card: $2500 Turing Tensor Terror Out Later This Month
    by Ryan Smith on December 3, 2018 8:00 AM EST
    https://www.anandtech.com/show/13668/nvidia-unveils-rtx-titan-2500-top-turing

    By this point we’ve seen most of NVIDIA’s 2018 Turing GPU product stack. After kicking things off with the Quadro RTX series, NVIDIA released a trio of consumer GeForce RTX cards, and following that the first Turing Tesla, the T4.

    Last year around this time we saw the launch of the Titan V at the Neural Information Processing Systems (NeurIPS) conference. It seems like that went well for the company, as they’ve once again picked that venue for the launch of their latest Titan card, the aptly named Titan RTX.

    Reply
  30. Tomi Engdahl says:

    Pentagram designed the prettiest computer chip you’ve ever seen
    https://www.fastcompany.com/90270782/pentagram-designed-the-prettiest-computer-chip-youve-ever-seen

    The microprocessor, built specifically to run machine learning algorithms, is covered in colorful tiles that help it stand out on a server rack.

    Reply
  31. Tomi Engdahl says:

    Vision AI developer kit combines AI and ML to push deep neural network models out to the intelligent edge
    https://iot.eetimes.com/vision-ai-developer-kit-combines-ai-and-ml-to-push-deep-neural-network-models-out-to-the-intelligent-edge/

    Companies are in the process of digitally transforming their business by using artificial intelligence (AI) and machine learning (ML). Currently this task is only possible once data is collected from internet-connected devices and stored in the cloud.

    The technology challenge with this approach is the strong dependency on a consistent connection to the cloud for sending and collecting data. As data volumes approach larger scales and deep learning requires increasingly more complex algorithms, the inevitable bottleneck will limit the quick adoption of AI and ML technologies.

    Currently, AI computations are feasible when vast, potentially bordering on infinite, amounts of computing resources are available from cloud resources. This requires an investment in expensive and powerful computational machines running at the edge. This requires continuous power supplies and direct connectivity to all sensor devices.

    Reply
  32. Tomi Engdahl says:

    Chris Velazco / Engadget:
    New Nvidia AI research project uses objects and scenery from within existing videos to build new interactive environments in realistic city landscapes — It all started with cities and — what else? — Gangnam Style. — Attendees of this year’s NeurIPS AI conference in Montreal can spend …

    NVIDIA’s new AI turns videos of the real world into virtual landscapes
    It all started with cities and — what else? — Gangnam Style.
    https://www.engadget.com/2018/12/03/nvidia-ai-video-to-video-synthesis/

    Attendees of this year’s NeurIPS AI conference in Montreal can spend a few moments driving through a virtual city, courtesy of NVIDIA. While that normally wouldn’t be much to get worked up over, the simulation is fascinating because of what made it possible. With the help of some clever machine learning techniques and a handy supercomputer, NVIDIA has cooked up a way for AI to chew on existing videos and use the objects and scenery found within them to build interactive environments.

    Reply
  33. Tomi Engdahl says:

    Ian Sample / The Guardian:
    DeepMind’s latest AI program AlphaFold wins international competition with its algorithm predicting 3D shapes of proteins, beating 97 entrants

    Google’s DeepMind predicts 3D shapes of proteins
    https://www.theguardian.com/science/2018/dec/02/google-deepminds-ai-program-alphafold-predicts-3d-shapes-of-proteins

    AI program’s understanding of proteins could usher in new era of medical progress

    Reply
  34. Tomi Engdahl says:

    Shall we have AI judging UK court cases? Top beak ponders the future
    ‘I have my doubts’ says Lord Chief Justice
    https://www.theregister.co.uk/2018/12/04/artificial_intelligence_judges_lord_chief_justice/

    The Lord Chief Justice (LCJ) of England and Wales thinks there is a place for articifial intelligence in the judicial process but isn’t losing any sleep over the security of his job just yet.

    Lord Burnett of Maldon, the top judge in England and Wales, gave a speech to the International Forum on Online Courts in which he mulled the idea that AI could “perform some, if not all” of the functions of him and his peers.

    Reply
  35. Tomi Engdahl says:

    China Plans to Build a Deep Sea Base Run Entirely by AI
    Robots, not humans, will run the show.
    https://futurism.com/deep-sea-base-ai-colony

    Artificial intelligences are about to get a place to call their own — and it’s located somewhere humans are unlikely to want to visit.

    scientists from the Chinese Academy of Sciences plan to construct a research base deep in the South China Sea, and they want artificially intelligent robots to run it.

    This base could be the “first artificial intelligence colony on Earth,” those involved in the project told the SCMP.

    Reply
  36. Tomi Engdahl says:

    Mary Jo Foley / ZDNet:
    Microsoft open sources the Open Neural Network Exchange runtime, part of its Windows ML platform, and makes Azure Machine Learning service generally available

    Microsoft open sources the inference engine at the heart of its Windows machine-learning platform
    https://www.zdnet.com/article/microsoft-open-sources-the-inference-engine-at-the-heart-of-its-windows-machine-learning-platform/

    Following its alliance with Facebook around the Open Neural Network Exchange (ONNX), Microsoft is open-sourcing the ONNX runtime engine for machine learning.

    Reply
  37. Tomi Engdahl says:

    Wave Rides AI-Enabled MIPS IP Licensing
    https://www.eetimes.com/document.asp?doc_id=1334038

    If you think Wave Computing (Campbell, Calif.) is just another startup building AI systems for servers and workstations used by data scientists, think again.

    In 2019, Wave is planting its banner in the licensing business.

    Wave is launching a fully-fledged licensing business that combines the company’s AI technologies with IPs from MIPS Technologies, acquired by Wave in June.

    Reply
  38. Tomi Engdahl says:

    Embedded FPGA Optimized for Machine Learning and Communication
    https://www.electronicdesign.com/embedded-revolution/embedded-fpga-optimized-machine-learning-and-communication?NL=ED-005&Issue=ED-005_20181205_ED-005_129&sfvc4enews=42&cl=article_1_b&utm_rid=CPG05000002750211&utm_campaign=21898&utm_medium=email&elq2=dbe1f43a4108430690f880af8d8f67c0

    Achronix’s Speedcore Gen 4 can be tailored for machine-learning applications as well as to deliver high-performance FPGA connectivity for embedded FPGAs.

    Reply
  39. Tomi Engdahl says:

    In the Coming Automated Economy, People Will Work for AI
    https://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/in-the-coming-automated-economy-people-will-work-for-ai

    The vets’ job: preparing data so that an artificial intelligence (AI) system can learn from it.

    “There’s a whole new industry sprouting on the shoulders of AI,” says Alegion CEO Nathaniel Gates in an interview with IEEE Spectrum. “We are employing people.”

    Reply
  40. Tomi Engdahl says:

    Where Facebook AI research moves nextu
    https://techcrunch.com/2018/12/05/where-facebook-ai-research-moves-next/?utm_source=tcfbpage&sr_share=facebook

    The company’s chief AI scientist reflects and predicts

    Reply
  41. Tomi Engdahl says:

    DeepMind Achieves Holy Grail: An AI That Can Master Games Like Chess and Go Without Human Help
    https://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/mb

    DeepMind, the London-based subsidiary of Alphabet, has created a system that can quickly master any game in the class that includes chess, Go, and Shogi, and do so without human guidance.

    The system, called AlphaZero, began its life last year by beating a DeepMind system that had been specialized just for Go.

    Reply
  42. Tomi Engdahl says:

    Microsoft calls on companies to adopt a facial recognition code of conduct
    https://techcrunch.com/2018/12/06/microsoft-calls-on-companies-to-adopt-a-facial-recognition-code-of-conduct/?utm_source=tcfbpage&sr_share=facebook

    Over the summer, Microsoft President Brad Smith called for governments to take a closer look at how facial detection technology is being implemented across the globe. This week, he returned with a similar message — only this time the executive is calling out fellow technology purveyors to help address myriad issues around the technology before it becomes too pervasive.

    https://blogs.microsoft.com/on-the-issues/2018/12/06/facial-recognition-its-time-for-action/

    Reply

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