Repeat the Question

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Here’s today at a glance:

• Just Keep Asking

• Sam Altman Unleashed

• Things happen

• AI artwork of the day

📝 Just Keep Asking

This research paper from the Tencent China team tries to find out whether just organizing the existing AI models we have into teams of agents that work together on a problem improves their performance, ie essence squeezing greater intelligence from a crowd of similar intelligences.

Paper Title: More Agents Is All You Need

Who: Team from Tencent China

What did they study:

• Does increasing the number of AI agents improve their performance on a task?

• In essence, does brute force scaling of AI agents work?

How did they do it?

• Create agents that in perform language model requests in two phases

  • In query phase, the input is iteratively fed into the same LLM or multiple LLMs to get multiple outputs

  • In the voting phase, a majority vote is taken on the best response

What did they find?

• Accuracy increases with the number of agents, notably at an ensemble size of 15 (either making 15 iterative calls to the same model or having multiple agents work on the same query), a Llama2 can match GPT3.5 single query, and a GPT3.5 can match a GPT4 single query.

• Performance gains increase initially with increasing difficulty but then hit a ceiling and then decline as problem complexity overwhelms the model

• Gains increase with the number of steps or iterations

What are the implications?

• You can increase intelligence with the same AI model just by asking the same question over and over iteratively

• This technique can improve raw performance for all AI/LLMs

• Brute force scaling works to a point but hits a ceiling

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💥 Sam Altman Unleashed

One of the greatest pleasures in seeing millennials found and run companies is the final falling away of the facade of fakeness that is expected of all businesspeople. OpenAI’s Sam Altman did not disappoint recently:

• Just before the Wall Street Journal report on the $7 trillion fundraising, possibly in response to a request for comment:

• Shortly thereafter, in response to his brother, Jack, who had complained of being forever titled “brother of Sam Altman,”

• In response to why he’s suddenly posting

• How many GPUs can you buy with $7 trillion?

• Was this a burn or just friendly banter? Alex Wang is the founder and CEO of ScaleAI, which does a lot of the human feedback training for large AI companies. Scale’s revenue tripled last year… off the backs of firms like OpenAI.

• Alternate uses of trillions

• More banter with brother Jack

• which continued

• Of course, it was not all play

• The inside joke below being that Roon (@tszzl), an OpenAI employee, had disappeared from Twitter for 3 days after a series of angsty adolescent tweets, leaving his 100k+ followers lost

• Mr Beast, probably the most famous and richest Youtuber of all time, hijacking the thread to make a plea for funding below

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🗞️ Things Happen

• “Researchers built a smartwatch heartbeat monitor that uses a slime mold for its operation. The slime mold has to be fed and cared for, so the users in the trial... developed an emotional attachment to it“, “she started calling me, you’re my little slime“ - so good

• Attention is really all you need, was from Nobel Laureate Herbert Simon in 1973: "The information-processing systems of our contemporary world swim in an exceedingly rich soup of information. In a world of this kind, the scarce resource is not information; it is processing capacity to attend to information. Attention is the chief bottleneck in organizational activity, and the bottleneck becomes narrower and narrower as we move to the top of organizations."

🖼️ AI Artwork Of The Day

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