Here’s How FTX Executives Secretly Spent $8 Billion in Customer Money https://www.wsj.com/finance/regulation/sbf-trial-ftx-customer-money-missing-6ba13914?reflink=integratedwebview_share

Intro for Pinecone

LlamaIndex Talk (AGI House + Truera + Pinecone)
https://docs.google.com/presentation/d/1mBhBgO7VFbp3gGPGx45-B6kcQRsLfbIK15s90DL5YXg/edit#slide=id.p

Also I got a ton of questions on how to do structured querying with a vector db. We have a guide here - the current guide is using Chroma but make sure to swap it out for Pinecone Autoretriever: https://docs.llamaindex.ai/en/stable/examples/vector_stores/chroma_auto_retriever.html Pinecone integration: https://docs.llamaindex.ai/en/stable/examples/vector_stores/PineconeIndexDemo.html

https://altos.vc/blog/cargo-cult-capital/

“In the South Seas there is a cargo cult of people. During the war they saw airplanes with lots of good materials, and they want the same thing to happen now. So they’ve arranged to make things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head to headphones and bars of bamboo sticking out like antennas — he’s the controller — and they wait for the airplanes to land. They’re doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn’t work. No airplanes land. So I call these things cargo cult science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land.”

There are service providers who market the fact that they have “access” to the top VCs. There are later stage funds who raise money based on claims that they can access deals of the top firms. There are also angels and “feeder funds” who hope to co-invest with top VCs by courting them from the other side. They cultivate relationships with powerful deal makers and give them first looks at deals so that they might invest once key “milestones” are met.

The cargo cult capital wheel keeps spinning around and around…as the crowds scramble to “get in” to what is hot (or what they speculate might get hot). Once funded, some entrepreneurs might feel like they are playing with the big boys. They retain the top law firms, the best PR agencies, and the most exclusive recruiters.

Armed with prestigious backing and exclusive relationships of kingmakers, the hottest companies hire the best talent that money can buy. The hired guns then create more frenzy…attracting even more capital to support ballooning headcounts and lofty salaries.

There are definite patterns followed by the cargo cult crowd. The form is perfect – the top deal makers, “world class” talent, a hot sector and business model du jour. Yet, ironically, I’d bet the next Bill Gates, Michael Dell, Phil Knight, Chuck Schwab, and Sam Walton are quietly going about doing their own thing…building companies based on business fundamentals.

Real entrepreneurs cut through the hype – they know what is essential. Their sense of pride doesn’t come from who they know or what others think – it comes from making a contribution and creating value. They will do it their own way – which won’t include wads of cash from outsiders. They figure out how to do more with less by using their brains, guts, and sweat.

Disruptive new entrants that topple giants belong to determined, frugal and independent minded entrepreneurs – and in their minds, the true stars are the customers they serve and their tireless co-workers who help turn dreams into realities.

🚨 BREAKING: GPT-4 image recognition already has a new competitor.

Open-sourced and completely free to use.
Introducing LLaVA: Large Language and Vision Assistant.
I compared the viral parking space photo on GPT-4 Vision to LLaVa, and it worked flawlessly (see video).

Link: https://llava-vl.github.io

Here's a side-by-side comparison of GPT-4 Vision vs. LLaVA

Do you know who sells the most sushi in the US each year?

The surprising answer: Kroger.

Kroger sells over 40 million pieces of sushi annually, raking in a staggering $600 million.

This was a huge surprise to me, where not too long ago sushi was once considered an experimental luxury.

Just like sushi became mainstream, niche content on platforms can turn into something massive.

Think about Minecraft; it started as a specialized interest and evolved into a global phenomenon.

The top-earning YouTuber from 2014 to 2017?

Minecrafters.

PewdiePie. DanTDM.

They built empires around their passion, and spawned the next gen of creators like Preston and Unspeakable .

When you operate on platforms with 1b+ users, the right niche can be a big opportunity.

As big as grocery store sushi. 🍣🍣🍱🍱

영국에서 공무원 남성 1만명의 건강 상태를 수십 년에 걸쳐 연구한 결과가 있습니다. 심장병에 의한 사망률을 비교했더니 글쎄 낮은 직위 쪽이 높은 직위보다 3배나 사망률이 높았어요.
이유는 업무 재량권이었다고 합니다. 고위직이 되면 책임과 압박감이 높아지지만 선택권과 자율권도 높아지죠. 재량권이 더 적다고 생각하는 사람들은 스트레스가 더 높고 심지어 사망에 다다를 수 있습니다.
삶을 통제한다는 느낌이란 이렇게 중요한가 봅니다. 생사를 가를 정도로 중요해요.
오늘도 우리 각자의 뜻을 살려 적극적으로 살아가 보자구요.

Q: How do you design an amazing user experience?

In the clip below, Airbnb co-founder and CEO Brian Chesky explains that one route to a great UX and word-of-mouth growth is designing the perfect experience for one person:

“How do you make something for a million people? I don’t know where to start. But if you pick one person, study them, and take their journey, you can actually build something really personal. You can design something and keep iterating until they love it. Don’t stop improving it until that person loves it, and you’re not allowed to move to the second person until the first person loves it. Then you get the second person and keep iterating until they love it. And so on.”

https://twitter.com/dair_ai/status/1711004647081562158

1/ LLMs Represent Space and Time - discovers that LLMs learn linear representations of space and time across multiple scales; the representations are robust to prompt variations and unified across different entity types; demonstrate that LLMs acquire fundamental structured knowledge such as space and time, claiming that language models learn beyond superficial statistics, but literal world models.

https://x.com/wesg52/status/1709551516577902782?s=20