Daily Archives: January 8, 2020

Unknown's avatar Rick's Cafe AI 6:58 pm on January 8, 2020
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The US just released 10 principles that it hopes will make AI safer

The principles (with my translation) are:

  1. Public trust in AI. The government must promote reliable, robust, and trustworthy AI applications.
  2. Public participation. The public should have a chance to provide feedback in all stages of the rule-making process.
  3. Scientific integrity and information quality. Policy decisions should be based on science. 
  4. Risk assessment and management. Agencies should decide which risks are and aren’t acceptable.
  5. Benefits and costs. Agencies should weigh the societal impacts of all proposed regulations.
  6. Flexibility. Any approach should be able to adapt to rapid changes and updates to AI applications.
  7. Fairness and nondiscrimination. Agencies should make sure AI systems don’t discriminate illegally.
  8. Disclosure and transparency. The public will trust AI only if it knows when and how it is being used.
  9. Safety and security. Agencies should keep all data used by AI systems safe and secure.
  10. Interagency coordination. Agencies should talk to one another to be consistent and predictable in AI-related policies.

Read More

#dod, #ic
Unknown's avatar Rick's Cafe AI 12:34 pm on January 8, 2020
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Machine Learning Can’t Handle Long-Term Time-Series Data

More precisely, today’s machine learning (ML) systems cannot infer a fractal structure from time series data.

This may come as a surprise because computers seem like they can understand time series data. After all, aren’t self-driving cars, AlphaStar and recurrent neural networks all evidence that today’s ML can handle time series data?

Nope. Read MOre

#recurrent-neural-networks
Unknown's avatar Rick's Cafe AI 12:32 pm on January 8, 2020
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What Is The Artificial Intelligence Of Things? When AI Meets IoT

Individually, the Internet of Things (IoT) and Artificial Intelligence (AI) are powerful technologies. When you combine AI and IoT, you get AIoT—the artificial intelligence of things. You can think of internet of things devices as the digital nervous system while artificial intelligence is the brain of a system. Read More

#iot

Unknown's avatar Rick's Cafe AI 12:26 pm on January 8, 2020
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Keeping Top AI Talent in the United States (CSET Report)

Talent is core to U.S. competitiveness in artificial intelligence, and international graduate students are a large source of AI talent for the United States. More than half of the AI workforce in the United States was born abroad, as were around two-thirds of current graduate students in AI-related fields. Tens of thousands of international students get AI-related degrees at U.S. universities every year. Retaining them, and ensuring a steady future talent inflow, is among the most important things the United States can do to address persistent domestic AI work-force shortages and to remain the global leader in AI.

… The good news is that student retention has historically been a core U.S. strength, with well over 80 percent of international U.S.-trained AI PhDs staying in the country, including those from AI competitors such as China.

…The bad news is that two trends are placing this U.S. strength in student retention at risk. Read More

#china-vs-us, #training
Unknown's avatar Rick's Cafe AI 12:18 pm on January 8, 2020
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The Next Big Thing in AI/ML is…

“The Next Big Thing in AI/ML is…” as the lead to an article is probably the most overused trope since “once upon a time”.  Seriously, just how many ‘next big things’ can there be?  Is your incredulity not stretched every time you read that?

It’s tempting to say that writers starting an article in this way should be flogged …except that yours truly did recently start one with “the next most IMPORTANT thing in AI/ML…”  Well that’s clearly different isn’t it – almost. Read More

#strategy
Unknown's avatar Rick's Cafe AI 12:12 pm on January 8, 2020
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These are the best free Artificial Intelligence educational (2020)

Deep learning is not a beginner-friendly subject — even for experienced software engineers and data scientists.

Deep learning is not a beginner-friendly subject — even for experienced software engineers and data scientists. If you’ve been Googling this subject, you may have been confused by the resources you’ve come across.

To find the best resources, we surveyed engineers on their favorite sources for deep learning, and these are what they recommended.

These educational resources include online courses, in-person courses, books, and videos. All are completely free and designed by leading professors, researchers, and industry professionals like Geoffrey Hinton, Yoshua Bengio, and Sebastian Thrun. Read More

#training