Microsoft’s new Bing browser powered by OpenAI’s ChatGPT is being played with by the public, raising many concerns with its responses.
Category: robotics/AI – Page 1,169
Multi-segment shapeshifter drones: The precursors to flying squid-bots
A remarkable group of drone prototypes from a team at the University of Tokyo takes multirotor complexity to the next level. These hypnotic flying robots are able to change their structural shape mid-air, creating some unprecedented capabilities.
ChatGPT creator Sam Altman says the world may not be ‘that far away from potentially scary’ AI and feels ‘regulation will be critical’
Microsoft’s AI-powered Bing unnerved some people recently with shocking responses.
Amid discussions and scrutiny, OpenAI CEO Sam Altman shared his thoughts on AI In a series of tweets on Sunday.
He warned the world may not be “that far from potentially scary” AI and said regulation will be “critical.”
Microsoft’s ChatGPT-powered Bing has unnerved some people recently, with shocking responses that range from snarky to overtly emotional.
Power of AI: World-renowned architects’ vision reimagined through cars
You can’t ride them, but you sure can dream about them.
The works of the world’s most famous architects are easy to recognize. They add beauty and grace to our landscape and brighten up even the gloomiest of neighborhoods.
Now, designers Moss and Fog have used AI-image generator MidJourney to produce cars in the style of the world’s most famous architects, and the results are both mesmerizing and invigorating. and Fog/Instagram.
Unique Datasets Will Take Generative AI Like ChatGPT to the Next Level
Chamath says that venture capitalist investors are looking for companies that can collect unique datasets. Proprietary unique datasets could be critical to having superior performance for ChatGPT like Generative AI.
The gradual march to AGI
Check out all the on-demand sessions from the Intelligent Security Summit here.
The coming of artificial general intelligence (AGI) — the ability of an artificial intelligence to understand or learn any intellectual task that a human can — is inevitable. Despite the predictions of many experts that AGI might never be achieved or will take hundreds of years to emerge, I believe it will be here within the next decade.
How can I be so certain? We already have the know-how to produce massive programs with the capacity for processing and analyzing reams of data faster and more accurately than a human ever could. And in truth, massive programs may not be necessary anyway. Given the structure of the neocortex (the part of the human brain we use to think) and the amount of DNA needed to define it, we may be able to create a complete AGI in a program as small as 7.5 megabytes.
AGI in sight: our look at the game board
Im still w/ Kurzweil at 2029, but:
+1. While I will also respect the request to not state them in the comments, I would bet that you could sample 10 ICML/NeurIPS/ICLR/AISTATS authors and learn about 10 well-defined, not entirely overlapping obstacles of this sort.
We don’t have any obstacle left in mind that we don’t expect to get overcome in more than 6 months after efforts are invested to take it down.
I don’t want people to skim this post and get the impression that this is a common view in ML.