3 AI misconceptions IT leaders must dispel


 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,”


  1. Tomi Engdahl says:

    He’s making artificial intelligence better by having it play poker

    Noam Brown was never very good at poker. But an artificially intelligent program he created became the first to beat the world’s top players in no-limit Texas Hold’em, the game’s most popular variant.

    In recent years, machines have defeated humans in checkers, chess, and Go—known as “perfect information” games, where both players know the exact state of play at any given point.

    Imperfect information games like poker, where hidden cards introduce strategies like bluffing, add another level of complexity

  2. Tomi Engdahl says:

    The US and China dominate investment in AI while Europe champions research. We’ve dug into the latest State of AI report to give you the key takeaways.


  3. Tomi Engdahl says:

    AI Trained on Old Scientific Papers Makes Discoveries Humans Missed

    Scientists used machine learning to reveal new scientific knowledge hidden in old research papers.

  4. Tomi Engdahl says:

    “Zero-shot” and “few-shot” learning—figuring out a task with little to no training—are important for AI. Here, researchers develop a system with “deep internal learning” that can sort out the internal structure of an image from scratch.


  5. Tomi Engdahl says:

    Facebook AI Pluribus defeats top poker professionals in 6-player Texas Hold ’em
    Pluribus beat five other human players with an unconventional bet-sizing strategy.

  6. Tomi Engdahl says:

    Carnegie Mellon and Facebook AI Beats
    Professionals in Six-Player Poker
    “Superhuman” card shark achieves new AI milestone

  7. Tomi Engdahl says:

    Daily Crunch: Neuralink prepares for brain-computer testing

    Elon Musk’s Neuralink looks to begin outfitting human brains with faster input and output starting next year

    Musk said that in the long term, Neuralink really is about figuring out a way to “achieve a sort of symbiosis with artificial intelligence.”

    For now, however, the plan is to use a robot that operates somewhat like a “sewing machine” to implant threads, which are incredibly thin, deep within a person’s brain tissue, where it will be capable of performing both read and write operations at very high data volume.

  8. Tomi Engdahl says:

    Elon Musk Announces Plan to ‘Merge’ Human Brains With AI

    Neuralink wants to start by treating brain injuries, eventually “achieve a symbiosis with artificial intelligence.”

    Elon Musk announced late Tuesday night that the final goal of Neuralink, his brain-machine interface startup, is to allow humans to “achieve a symbiosis with artificial intelligence,” and that by “merging with AI,” humans will be able to keep up with AI. Musk plans to begin human trials on an early version of Neuralink intended to treat brain injuries next year.

  9. Tomi Engdahl says:

    With This AI, 60 Percent of Patients Who Had Surgery Could Have Avoided It

    An estimated 800,000 patients in the United States are incidentally diagnosed with pancreatic cysts each year, and doctors have no good way of telling which cysts harbor a deadly form of cancer and which are benign. This ambiguity results in thousands of unnecessary surgeries: One study found that up to 78 percent of cysts for which a patient was referred to surgery ended up being not cancerous.

  10. Tomi Engdahl says:

    We all know the technology is expand day by day and we see most of all technology is automaic principle work. That’s why in this video i will teach you about What is Artifical Intelligence? So, for more information about A.i watch this video till END.!!!


  11. Tomi Engdahl says:

    Microsoft invests $1 billion in artificial intelligence project co-founded by Elon Musk

    Microsoft and OpenAI announced a new partnership to build artificial general intelligence to tackle more complex tasks than AI.
    Microsoft will invest $1 billion in OpenAI as part of the project, the companies said.
    While today’s AI can tackle simple tasks, the companies said AGI will be able to take on more “multidisciplinary problems.”

  12. Tomi Engdahl says:

    Microsoft invests $1 billion in OpenAI in new multiyear partnership

  13. Tomi Engdahl says:


    But for deep learning, high precision is not necessarily desirable. “Deep learning, in fact, performs better with lower precision,” says Pradeep Dubey, who directs the Parallel Computing Lab at Intel. While he acknowledges that sounds confusing, his explanation is the when you’re training deep learning models, “you need an ability to generalize.”

    According to Dubey, IEEE’s FP16 format reduces the dynamic range too much in an effort to keep more bits for precision, but again, that’s not the tradeoff you want for deep learning computations. What often happens is that with FP16, the model doesn’t converge, so you end up needing to tune the hyperparameters – things like the learning rate, batch size, and weight decay.

    Thus was born bfloat16, affectionately known as 16-bit “brain” floating point. Developed originally by Google and implemented in its third generation Tensor Processing Unit (TPU), bfloat16 has attracted some important backers.

  14. Tomi Engdahl says:

    A “FaceApp” to enlarge breasts? It’s here, and there’s more to it than you may think.

    The whole world has been taken by storm by “FaceApp”: a new app that allows you to edit a picture of yourself and see how you’d look like older, younger, with different hair style and so on. As soon as I saw the app, I recognized the state-of-the-art Artificial Intelligence algorithms that are behind it. Since I’ve been following these algorithms for a while, I wondered:
    We have an incredibly powerful technology available and all we can do with it is internet memes?

  15. Tomi Engdahl says:

    Putting Machine Learning Into the Home and Onto the Internet of Things
    Want to buy a smart camera for $20?

  16. Tomi Engdahl says:

    A new AI-based tool can detect the telltale sign of a deepfake image at the level of single pixels #deepfake #AI #ML

    A Two-Track Algorithm To Detect Deepfake Images

  17. Tomi Engdahl says:

    The Military Secretly Built An “Artificial Brain” Called Sentient

    Since 2010, American intelligence agencies have been developing a top-secret “artificial brain” military AI system that they named — seriously — “Sentient.”


  18. Tomi Engdahl says:

    Will Knight / MIT Technology Review:
    Researchers developed AI that learned chess not by playing but by analyzing reactions of expert commentators in text form to evaluate the quality of the moves

    Instead of practicing, this AI mastered chess by reading about it
    Machines that appreciate “brilliant” and “dumb” chess moves could learn to play the game—and do other things—more efficiently.

  19. Tomi Engdahl says:

    AI lie detector developed for airport security

    Virtual border guard that asks travellers questions and assesses their answers trialled in airports

    A group of researchers are quietly commercialising an artificial intelligence-driven lie detector, which they hope will be the future of airport security.

  20. Tomi Engdahl says:

    Holy Grail supercomputer ‘will have human-level artificial intelligence’ in just 5 years

    SCIENTISTS battling to build the first supercomputer with human-level intelligence think size could be the key to the Holy Grail of AI breakthroughs.

    Microsoft has recently injected $1 billion into an artificial intelligence research group co-founded by tech genius Elon Musk which is aiming to be the first to build a computer which matches its creators for intelligence.

    The group, OpenAI, even thinks such a milestone could happen inside five years.

    Currently, supercomputers can do specific tasks better than humans — such as playing chess — but don’t have what has been dubbed “Artificial general intelligence”.

  21. Tomi Engdahl says:

    Artificial Intelligence
    China has started a grand experiment in AI education. It could reshape how the world learns.


    In recent years, the country has rushed to pursue “intelligent education.” Now its billion-dollar ed-tech companies are planning to export their vision overseas.

  22. Tomi Engdahl says:

    Sharon Terlep / Wall Street Journal:
    How companies use AI in customer service: some to serve clients better, and some to find the “breakpoint” at which their service is so bad that a customer quits

    Everyone Hates Customer Service. This Is Why.

    Technology lets companies see how badly they can treat consumers, right up until the moment they bolt

  23. Tomi Engdahl says:

    Social Media Companies Remind Us It Is Still Hard To Replace Humans With AI

    Companies have rushed to embrace deep learning’s potential in their efforts to automate their enterprises, often with an eye towards replacing as much of their human workforce as possible or to scale their operations without expanding their hiring. An endless stream of success stories tout AI’s success in replacing an ever-growing array of traditionally automation-resistant jobs, while developers are hard at work finding ways to replace the rest of them. Yet social media platforms give pause to this idea that deep learning is quite at the inflection point of causing a wave of job displacement.

  24. Tomi Engdahl says:

    EfficientNet-EdgeTPU are a family of image classification neural network models customized for deployment on Google Edge TPU.


  25. Tomi Engdahl says:

    Nvidia Teaching Robots To Master IKEA Kitchens

    The current wave of excitement around machine learning kicked off when graphics processors were repurposed to make training deep neural networks practical. Nvidia found themselves the engine of a new revolution and seized their opportunity to help push frontiers of research. Their research lab in Seattle will focus on one such field: making robots smart enough to work alongside humans in an IKEA kitchen.

  26. Tomi Engdahl says:

    Specialized AI Chips Hold Both Promise and Peril for Developers

    When it comes to the compute-intensive field of AI, hardware vendors are reviving the performance gains we enjoyed at the height of Moore’s Law. The gains come from a new generation of specialized chips for AI applications like deep learning. But the fragmented microchip marketplace that’s emerging will lead to some hard choices for developers.

  27. Tomi Engdahl says:

    Sheri Fink / New York Times:
    Interviews and documents show that One Concern, which wants to use AI to help emergency responders in disasters, dangerously exaggerated its tools’ abilities

    This High-Tech Solution to Disaster Response May Be Too Good to Be True

    Major cities are turning to a Silicon Valley start-up to help save lives in an emergency. But some fear its promise has been dangerously exaggerated.

    The company called One Concern has all the characteristics of a buzzy and promising Silicon Valley start-up: young founders from Stanford, tens of millions of dollars in venture capital and a board with prominent names.

    Its particular niche is disaster response. And it markets a way to use artificial intelligence to address one of the most vexing issues facing emergency responders in disasters: figuring out where people need help in time to save them.

    But when T.J. McDonald, who works for Seattle’s office of emergency management, reviewed a simulated earthquake on the company’s damage prediction platform, he spotted problems.

    The error? The simulation, the company acknowledged, missed many commercial areas because damage calculations relied largely on residential census data.

    interviews and documents show the company has often exaggerated its tools’ abilities and has kept outside experts from reviewing its methodology.

    Some critics even suggest that shortcomings in One Concern’s approach could jeopardize lives.

    The company then revised its product twice, adding new sources of building data in Seattle, including satellite imagery, and updating its algorithms. That fixed some issues, but introduced others.

    The Costco now appeared in the earthquake simulation, but “the entire University of Washington dropped out,”

    More troubling, each update produced vastly different damage predictions when simulating the same earthquake.

    “One of the major harms is the potential to divert attention from people who actually need assistance,”

    Mr. Wani tells a dramatic company origin story to underline his pitch that the world of disaster response is ripe for disruption.

    Officials in San Francisco were among the service’s earliest fans.

    “I was totally blown away,” said Anne Kronenberg, the city’s former emergency management director. The city was using a free FEMA product, Hazus, to estimate earthquake damage. She found it technically demanding. One Concern’s product, by contrast, depicted block-by-block damage in a web browser and promised to refine predictions with artificial intelligence as on-the-ground reports were fed back into it.

    Other technology companies, including Google and Fathom, are applying machine learning and other analytical techniques to flood forecasting, with the latter publishing results in major scientific journals.


  28. Tomi Engdahl says:

    4 misconceptions about ethics and bias in AI
    As artificial intelligence increasingly affects our lives, we must consider how algorithms affect real people

  29. Tomi Engdahl says:

    Khari Johnson / VentureBeat:
    Facebook AI Research, DeepMind, NYU, and University of Washington debut SuperGLUE, a series of AI benchmarks to measure natural language processing performance

    AI researchers launch SuperGLUE, a rigorous benchmark for language understanding

    Facebook AI Research, together with Google’s DeepMind, University of Washington, and New York University, today introduced SuperGLUE, a series of benchmark tasks to measure the performance of modern, high performance language-understanding AI.


  30. Tomi Engdahl says:

    Cloud API

  31. Tomi Engdahl says:

    Machine Learning for Creators?
    Taking the data science out of machine learning

    I’ve argued in the past that the biggest growth area in machine learning practice over the next year or two could well be around inferencing, rather than training. Because it is the existence of pre-trained models that let us easily and quickly build prototypes and projects on top of machine learning. Which is, it turns out, what most people that aren’t focused on the machine learning itself but instead just want to something accomplished, want.


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