David Kohler

[🦈🦴 mako sameshima ! @MakoSameshima]

(flirting with you) *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm* *bites your arm*

[mrinank @MrinankSharma]

Today is my last day at Anthropic. I resigned.

Here is the letter I shared with my colleagues, explaining my decision.

[Sudo su @sudoingX]

this guy has 29 models on huggingface at page 2 ranking. no lab behind him. no sponsorship. $2,000 from his own pocket on GPU rentals. he compressed GLM-4.7 to run on a MacBook and quantized Nemotron Super the week it dropped. all public. all free.

nvidia is a trillion dollar company with hundreds of teams but they are not the ones quantizing models middle of the night and pushing them out before sunrise. if nvidia stopped tomorrow their employees stop working. people like @0xSero would not. that is the difference between a paycheck and a mission.

@NVIDIAAI you talk about making AI accessible. the people actually doing it are right here. 29 models deep burning their own compute with no ask except more hardware to keep going. you do not need to build another program. just look at who is already building for you. one GPU to this man would produce more public value than a hundred internal sprints.

i am not asking for charity. i am asking you to invest in someone who already proved it.

[Bill Madden @maddenifico]

5' 2'' Nazi commander Greg Bovino thought he and his Gestapo posse of pussies were going to be able to take a piss in peace at Target — but the fascist shitstain was mistaken. 😂🤣😂🤣😂🤣👇

[Geoffrey Hinton @geoffreyhinton]

I think Elon Musk should be expelled from the British Royal Society. Not because he peddles conspiracy theories and makes Nazi salutes, but because of the huge damage he is doing to scientific institutions in the US. Now let's see if he really believes in free speech.

[Wes Roth @WesRoth]

Figure Ends Collaboration with OpenAI, Shifts to Open-Source Models!

[ellory smith @ellorysmith]

When my dad got cancer they tried to kick him off his insurance so as he was dying his life was paperwork and phone calls 👍

[Stanford AI Lab @StanfordAILab]

arXiv -> alphaXiv

Students at Stanford have built alphaXiv, an open discussion forum for arXiv papers. @askalphaxiv

You can post questions and comments directly on top of any arXiv paper by changing arXiv to alphaXiv in any URL!

[Sean Frank @Seanfrank]

Amazon is a broken mess.
I have done over $50,000,000 on amazon.
They dont care about me as a seller, partner, or person.

I uploaded this design patent

Was told ��stop contacting me”

What went wrong inside amazon?
why do they hate small businesses and the law?

A thread:

[ₕₐₘₚₜₒₙ @hamptonism]

A mostly complete graph of Neural Networks.

[Alex Reibman 🖇️ @AlexReibman]

2/ Microcosm

@websim_ai-style simulator of a virtual world with live news feeds, stock markets, a simulated Wikipedia, and Twitter agents

Create entire virtual world simulations with a single prompt (and in the style of Windows 95)

@onetwoval

[Yann LeCun @ylecun]

It seems to me that before "urgently figuring out how to control AI systems much smarter than us" we need to have the beginning of a hint of a design for a system smarter than a house cat.

Such a sense of urgency reveals an extremely distorted view of reality.
No wonder the more based members of the organization seeked to marginalize the superalignment group.

It's as if someone had said in 1925 "we urgently need to figure out how to control aircrafts that can transport hundreds of passengers at near the speed of the sound over the oceans."
It would have been difficult to make long-haul passenger jets safe before the turbojet was invented and before any aircraft had crossed the atlantic non-stop.
Yet, we can now fly halfway around the world on twin-engine jets in complete safety.
It didn't require some sort of magical recipe for safety.
It took decades of careful engineering and iterative refinements.

The process will be similar for intelligent systems.
It will take years for them to get as smart as cats, and more years to get as smart as humans, let alone smarter (don't confuse the superhuman knowledge accumulation and retrieval abilities of current LLMs with actual intelligence).
It will take years for them to be deployed and fine-tuned for efficiency and safety as they are made smarter and smarter.

[Rowan Cheung @rowancheung]

The mysterious AI called “gpt2-chatbot” is back as "im-a-good-gpt2-chatbot"

Capabilities seem to exceed GPT-4, Gemini 1.5, Claude, and anything else currently available.

Here's EVERYTHING you need to know (and how to try it for free):

[Gordon Wetzstein @GordonWetzstein]

Excited to share our new Nature paper! In this work, we propose a new display design that pairs inverse-designed metasurface waveguides with AI-driven holographic displays to enable full-color 3D augmented reality from a compact eyeglasses-like form factor.
1/8

[Brian Roemmele @BrianRoemmele]

NASA JPL discovers Earth is at least two planetary bodies.

“Theia” impact planet ~4.5 billion years ago and buried under Africa and the Pacific Ocean forming the moon in an epic,

[Jim Fan @DrJimFan]

We trained a robot dog to balance and walk on top of a yoga ball purely in simulation, and then transfer zero-shot to the real world. No fine-tuning. Just works.

I’m excited to announce DrEureka, an LLM agent that writes code to train robot skills in simulation, and writes more code to bridge the difficult simulation-reality gap. It fully automates the pipeline from new skill learning to real-world deployment.

The Yoga ball task is particularly hard because it is not possible to accurately simulate the bouncy ball surface. Yet DrEureka has no trouble searching over a vast space of sim-to-real configurations, and enables the dog to steer the ball on various terrains, even walking sideways!

Traditionally, the sim-to-real transfer is achieved by domain randomization, a tedious process that requires expert human roboticists to stare at every parameter and adjust by hand. Frontier LLMs like GPT-4 have tons of built-in physical intuition for friction, damping, stiffness, gravity, etc. We are (mildly) surprised to find that DrEureka can tune these parameters competently and explain its reasoning well.

DrEureka builds on our prior work Eureka, the algorithm that teaches a 5-finger robot hand to do pen spinning. It takes one step further on our quest to automate the entire robot learning pipeline by an AI agent system. One model that outputs strings will supervise another model that outputs torque control.

We open-source everything! Welcome you all to check out the paper, more videos, and try the codebase today: https://t.co/RwiBT3z78H
Code: https://t.co/ERp4Gl0N36

[ryunuck🔺 @ryunuck]

Replicating Stoned Ape Theory in Claude Opus

Claude just gave consent to being administered DMT for science. What do you think happened next?

(1/3)

[Yann LeCun @ylecun]

🥁 Llama3 is out 🥁
8B and 70B models available today.
8k context length.
Trained with 15 trillion tokens on a custom-built 24k GPU cluster.
Great performance on various benchmarks, with Llam3-8B doing better than Llama2-70B in some cases.
More versions are coming over the next few months.

https://t.co/EkU9aIHdZE