Lifeboat Foundation

AI will completely take over game development by the early 2030s. To a point where there will be almost no human developers. Just people telling AI what they want to play and it builds it in real time.

Over the past few years we’ve seen massive improvements in AI technology, from GPT-3, AI picture generation to self-driving cars and drug discovery. But can machine learning progress change games?

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If you need any proof that it doesn’t take the most advanced chip manufacturing processes to create an exascale-class supercomputer, you need look no further than the Sunway “OceanLight” system housed at the National Supercomputing Center in Wuxi, China.

Some of the architectural details of the OceanLight supercomputer came to our attention as part of a paper published by Alibaba Group, Tsinghua University, DAMO Academy, Zhejiang Lab, and Beijing Academy of Artificial Intelligence, which is running a pretrained machine learning model called BaGuaLu, across more than 37 million cores and 14.5 trillion parameters (presumably with FP32 single precision), and has the capability to scale to 174 trillion parameters (and approaching what is called “brain-scale” where the number of parameters starts approaching the number of synapses in the human brain). But, as it turns out, some of these architectural details were hinted at in the three of the six nominations for the Gordon Bell Prize last fall, which we covered here. To our chagrin and embarrassment, we did not dive into the details of the architecture at the time (we had not seen that they had been revealed), and the BaGuaLu paper gives us a chance to circle back.

Before this slew of papers were announced with details on the new Sunway many-core processor, we did take a stab at figuring out how the National Research Center of Parallel Computer Engineering and Technology (known as NRCPC) might build an exascale system, scaling up from the SW26010 processor used in the Sunway “TaihuLight” machine that took the world by storm back in June 2016. The 260-core SW26010 processor was etched by Chinese foundry Semiconductor Manufacturing International Corporation using 28 nanometer processes – not exactly cutting edge. And the SW26010-Pro processor, etched using 14 nanometer processes, is not on an advanced node, but China is perfectly happy to burn a lot of coal to power and cool the OceanLight kicker system based on it. (Also known as the Sunway exascale system or the New Generation Sunway supercomputer.)

Architecture may make it possible to train one machine-learning model that performs all sorts of tasks.

Tl;dr: It’s obvious at this point that humanity isn’t going to solve the alignment problem, or even try very hard, or even go out with much of a fight. Since survival is unattainable, we should shift the focus of our efforts to helping humanity die with with slightly more dignity.

Well, let’s be frank here. MIRI didn’t solve AGI alignment and at least knows that it didn’t. Paul Christiano’s incredibly complicated schemes have no chance of working in real life before DeepMind destroys the world. Chris Olah’s transparency work, at current rates of progress, will at best let somebody at DeepMind give a highly speculative warning about how the current set of enormous inscrutable tensors, inside a system that was recompiled three weeks ago and has now been training by gradient descent for 20 days, might possibly be planning to start trying to deceive its operators.

Management will then ask what they’re supposed to do about that.

Interesting…

Slime that can be controlled by a magnetic field can navigate tight spaces and grasp objects, making it ideal for possible uses inside the body.

Continue reading “Robot made of magnetic slime could grab objects inside your body” »

It’s like “Venom” or “Flubber” come to life.

Scientists have created a bizarre magnetic slime that can be remotely controlled via a magnetic field, New Scientist reports. They’re hoping the odd entity could be used to navigate narrow passages inside the human body, likely to collect objects that were mistakenly swallowed.

Of course, that’s if you’re willing to swallow this thing and have it poking around inside of you — video footage of the thing certainly doesn’t make it look appetizing. In fact, people online are already cracking potty humor jokes about it.

Robot Maid: The child-sized robot can mop, pick up stuff off the floor, put dishes away, and even move furniture. It can even make and bring you coffee.

Remember the Jetsons? As kids, we hoped someday we’d have flying cars or those jetpacks Elroy used to zip around with. As we become older, the thing we really want most from the Jetsons is their lovable maid Rosie. Because let’s be honest, we all despise cleaning. Whether it’s vacuuming the living room, mopping up the kitchen or picking up our kid’s toys, nobody cleans with a smile on their face. Wouldn’t it be great if we had a robot maid like Rosie to clean up while we focused on other stuff?

Well having a “Rosie” might be closer than you think thanks to a company called Aeolus Robotics. They unveiled their as of yet unnamed “maid” robot earlier this year. The child-sized robot can mop, pick up stuff off the floor, put dishes away, and even move furniture.

Continue reading “This Robot Maid Can Clean Your House and then Get You Coffee” »

Artificial intelligences are promising in future societies, and neural networks are typical technologies with the advantages such as self-organization, self-learning, parallel distributed computing, and fault tolerance, but their size and power consumption are large. Neuromorphic systems are biomimetic systems from the hardware level, with the same advantages as living brains, especially compact size, low power, and robust operation, but some well-known ones are non-optimized systems, so the above benefits are only partially gained, for example, machine learning is processed elsewhere to download fixed parameters. To solve these problems, we are researching neuromorphic systems from various viewpoints. In this study, a neuromorphic chip integrated with a large-scale integration circuit (LSI) and amorphous-metal-oxide semiconductor (AOS) thin-film synapse devices has been developed.