🤖 AI Brief: AI reads minds, ChatGPT vs. open-source, and OpenAI's $540M burn

One clear theme for this week’s AI news stands out: no one really knows where we’re all headed.

You have the “godfather” of AI claiming “bad things” are ahead, but not knowing what, a leaked Google paper saying open-source will outpace closed-source models like Bard and ChatGPT, and entire companies seeing 50% stock drops as AI disrupts their business models.

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In this issue:

• 📉 AI continues to impact the job landscape on multiple fronts

• 💥 Chegg’s valuation blew up after disclosing ChatGPT ate their luunch

• 🤖 Leaked Google memo says open-source will beat Bard and ChatGPT

• 💰️ OpenAI burned $540M last year, wants $100B more to develop AGI

• 🏗️ Society continues to grapple with the AI future

• 🧠 AI can now read human thoughts, plus other science experiments

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📉 AI continues to impact the job landscape

We’re in the midst of seeing society reconfigure itself as generative AI rapidly impacts numerous functions.

• Hollywood writers are on strike right now, and one of the concerns they have is generative AI will put additional pressure on their declining wages as their profession is confronted with numerous headwinds. Read our full breakdown here.

• Creative roles in general face enormous pressure, with one veteran writer sharing on Reddit that their client base had virtually vanished overnight. The feedback? “Some of them admitted that I am obviously better than ChatGPT, but $0 overhead can't be beat and is worth the decrease in quality.”

• IBM announced that it would pause hiring on 26k non-customer-facing roles. The reason? IBM’s CEO explained: “I could easily see 30% of that getting replaced by AI and automation over a five-year period.”

💥 Entire companies are finding themselves vulnerable to AI’s rapid pace of disruption

Chegg’s nearly 50% stock drop this week is expected to be just the first of many companies experiencing an existential crisis.

• Despite announcing their own GPT-4 AI chatbot in the works, investors simply aren’t buying that a chatbot is going to save Chegg’s business

• This is a warning sign to other companies who think AI will protect their existing business lines. Read our full analysis here.

🤖 Is the future of AI open-source?

That’s the major discussion in the tech community right now, and it’s attracting opinions on all sides.

• The catalyst is a leaked Google memo written by a senior AI engineer claiming “we have no moat, and neither does OpenAI.”

• The explosive claim at the heart of this memo: open-source will overtake closed systems like GPT-4 and Bard, and the author points to numerous examples of how fast open-source has advanced since Meta’s LLaMA LLM model leaked into the wild.

• Substantial amounts of venture funding is going towards closed-source foundational models right. Anthropic just raised another $850M, and Inflection launched its own chatbot this week on heels of a $225M seed round.

• Not everyone believes it, however, and skeptics are pointing to numerous examples of integrations, developers, and enterprise contracts as moats. Our full breakdown here looks at a number of these skeptical arguments.

💰️ OpenAI burned $540M last year, wants $100B more to develop AGI

OpenAI is a private company, so getting a peek into its finances is extremely interesting. The leak comes courtesy of The Information, one of Silicon Valley’s most trusted media publications, so we have reason to believe these numbers hold water.

• The company burned $540M in 2022 to develop ChatGPT, and expects to burn even more this year despite some rocketship revenue numbers (it thinks it’ll beat $200M revenue in 2023).

• It’s got a lot of rocket fuel though, having secured $10 billion in funding from Microsoft this year with priority access to computing resources, which are rationed out in this era of high demand

• But could it all be for naught? That’s what the leaked Google memo is saying: LLMs with comparative quality can now be trained for hundreds, not billions, of dollars.

• Still, OpenAI employees are able to celebrate a bit. News broke this week of a $300M share sale at a nearly $30B valuation. That’s quite some cheddar!

🏗️ Society continues to grapple with the AI future

Governments continue to play catch-up on AI, as humans wrestle with AI’s position in the world.

• AI’s own “godfather” who created neural networks has a warning: “bad things” lie ahead as AI’s progress proceeds.

• The White House convened a meeting of AI leaders from Google, Microsoft, OpenAI, Anthropic and more to discuss AI regulations and safety. But with open source models running amok, is it too late?

🧪 Science Experiments

GPT AI can now decode your thoughts

Is mind-reading possible? We’re getting there when GPT AI can now decode fMRI signals with up to 82% accuracy. Our breakdown of this breakthrough research went viral this week (1.5M impressions!), and we consider this a milestone for AI tech.

Vicuna-13B: the open source model that’s 92% as good as ChatGPT

The leaked Google memo cites this as one of the main reasons ChatGPT will get outpaced. Based on Meta’s leaked LLaMA LLM, then fine-tuned on 70k ChatGPT conversations for just $300, it claims 92% of the quality of ChatGPT.

• Test it here for yourself and let me know your thoughts!

• Here’s the full research if you’re curious.

Nvidia team teaches AI to learn tennis from just watching broadcast videos

Wow. Talk about cool — AI was unleashed on tennis footage, and it learned how to play virtual tennis. Backhand slice, forehand topspin were just some of the moves learned all from watching videos.

• See the methodology and video examples here.

Dreampaint enables in-painting of e-commerce models for virtual-try on

We’ve had 3D-try ons and AR 3D furniture for awhile. But this is something new – pairing Stable Diffusion with a customized in-painting engine to easily render virtual clothes, furniture and more from images.

• The full research paper is here.

AI Chat Assistants can improve conversations about divisive topics

Could AI chatbots actually help our society in unexpected ways? Researchers found that chatbots had a tendency to make polarized subjects feel understood, while not changing the content of its responses. They tested this on a tried and true topic: gun control.

• Read the full paper here.

• Similarly, LLMs have been found to help humans reframe negative thoughts in another study.

Transformer memory can be mass edited

Researchers found a new technique to enable thousands of insertions vs. updating single associations in a transformer model. If implemented successfully, could be a powerful way to replace obsolete information or add specialized knowledge in LLMs in a scalable and affordable manner.

• Read the full paper here.

OpenAI released Shap-E, a text-to-3D-model generator

Text-to-image is old school now. Text-to-3d-models is where a lot of the frontier tech is playing, and OpenAI jumped into the ring this week with Shap-E. This is an early proof-of-concept but expect AI tech on this front to rapidly improve.

• See it here

That’s it! Have a great week!

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