“I’m still working on being a good CEO,” Jensen Huang said in an interview at his alma mater, Stanford University.
Artificial general intelligence (AGI) — often referred to as “strong AI,” “full AI,” “human-level AI” or “general intelligent action” — represents a significant future leap in the field of artificial intelligence. Unlike narrow AI, which is tailored for specific tasks, such as detecting product flaws, summarizing the news, or building you a website, AGI will be able to perform a broad spectrum of cognitive tasks at or above human levels. Addressing the press this week at Nvidia’s annual GTC developer conference, CEO Jensen Huang appeared to be getting really bored of discussing the subject — not least because he finds himself misquoted a lot, he says.
The frequency of the question makes sense: The concept raises existential questions about humanity’s role in and control of a future where machines can outthink, outlearn and outperform humans in virtually every domain. The core of this concern lies in the unpredictability of AGI’s decision-making processes and objectives, which might not align with human values or priorities (a concept explored in-depth in science fiction since at least the 1940s). There’s concern that once AGI reaches a certain level of autonomy and capability, it might become impossible to contain or control, leading to scenarios where its actions cannot be predicted or reversed.
When sensationalist press asks for a timeframe, it is often baiting AI professionals into putting a timeline on the end of humanity — or at least the current status quo. Needless to say, AI CEOs aren’t always eager to tackle the subject.
From abstract-looking cloud formations to roars of snow machines on ski slopes, the transformation of liquid water into solid ice touches many facets of life. Water’s freezing point is generally accepted to be 32 degrees Fahrenheit. But that is due to ice nucleation—impurities in everyday water raise its freezing point to this temperature. Now, researchers unveil a theoretical model that shows how specific structural details on surfaces can influence water’s freezing point.
A research team led by Prof. Meng Guowen and Prof. Han Fangming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, together with Prof. Wei Bingqing from the University of Delaware, miniaturized line-filtering capacitors with “matryoshka doll” structure electrodes, providing a high-performance and space-saving solution for line-filtering applications.
The Tesla FSD V12.3 performs well in snowy conditions, demonstrating good acceleration, braking, and handling capabilities, as well as safety features such as pausing at intersections without stop signs.
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Spring weather brings welcome conditions for flowers and plant life to bloom across the land. The right mixture of temperature, moisture, and light helps keep the green world vibrant.
Questions to inspire discussion.
What improvements does Tesla’s FSD v12.3 update show?
—Tesla’s FSD v12.3 update shows significant improvements in driving behavior, safety, and comfort, but still has some remaining issues to be addressed.
Tesla FSD v12.3 in Austin, Texas demonstrates significant improvements in smoothness, confidence, and assertive driving, with better safety, natural stops, improved navigation, and a sense of understanding, showing promising long-term implications for Tesla.
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Monitoring levels of DNA shed by tumors and circulating in the bloodstream could help doctors accurately assess how gastroesophageal cancers are responding to treatment, and potentially predict future prognosis, suggests a new study led by researchers at the Johns Hopkins Kimmel Cancer Center and its Bloomberg–Kimmel Institute for Cancer Immunotherapy.
