*"This is a 1 hour general-audience introduction to Large Language Models: the core technical component behind systems like ChatGPT, Claude, and Bard. What they are, where they are headed, comparisons and analogies to present-day operating systems, and some of the security-related challenges of this new computing paradigm."*

Andrej Karpathy - Intro to Large Language Models [Video]

Hi I'm Jeremy. I'm building this site because I'm not satisfied with other online community type websites and their lack of innovation (see the /about page). The goal is to make a superior, more open, and more decentralized online community.

The site is still in early stages in active development (see the dev masterthread here: https://zsync.xyz/p/zsync-dev-update-masterthread)

Join us if this sounds interesting! Feel free to send me any feedback or reach out directly!

*"While self-correction has shown promise in improving LLM outputs in terms of style and quality (e.g. Chen et al., 2023; Madaan et al., 2023), recent attempts to self-correct logical or reasoning errors often cause correct answers to become incorrect, resulting in worse performances overall (Huang et al., 2023). In this paper, we break down the self-correction process into two core components: mistake finding and output correction. For mistake finding, we release BIG-Bench Mistake, a dataset of logical mistakes in Chain-of-Thought reasoning traces. We provide benchmark numbers for several state-of-the-art LLMs, and demonstrate that LLMs generally struggle with finding logical mistakes. For output correction, we propose a backtracking method which provides large improvements when given information on mistake location. We construe backtracking as a lightweight alternative to reinforcement learning methods, and show that it remains effective with a reward model at 60-70% accuracy."*

LLMs cannot find reasoning errors, but can correct them

The New PS5 SLIM is just around the corner! 5 things you need to know.

Show HN: <https://news.ycombinator.com/item?id=38285228>

*"I built a simple React/Python app that takes screenshots of websites and converts them to clean HTML/Tailwind code.*

*It uses GPT-4 Vision to generate the code, and DALL-E 3 to create placeholder images.*

*To run it, all you need is an OpenAI key with GPT vision access.*

*I’m quite pleased with how well it works most of the time. Sometimes, the image generations can be hilariously off. See here for a replica of Taylor Swift’s Instagram page: [https://streamable.com/70gow1](https://streamable.com/70gow1) I initially had a hard time getting it to work on full page screenshots. GPT4 would code up the first couple of sections and then, get lazy and output placeholder comments for the rest of the page. With some prompt engineering, full page screenshots work a whole lot better now. It’s great for landing pages."*

Convert any screenshot into clean HTML code using GPT Vision (OSS tool)

Bitcoin exchange-traded funds (ETFs) have gained popularity as a financial instrument, offering several benefits for investors. Here are some key advantages associated with Bitcoin ETFs:

1. **Accessibility and Convenience:**

   - **Mainstream Investment Vehicle:** Bitcoin ETFs provide a familiar and regulated investment vehicle for traditional investors who may be hesitant to directly invest in cryptocurrencies. This can attract a broader range of investors, including institutional players.
   - **Ease of Trading:** ETFs are traded on traditional stock exchanges, making them accessible through regular brokerage accounts. This eliminates the need for investors to set up and manage digital wallets, private keys, and navigate cryptocurrency exchanges.

2. **Regulatory Oversight:**

   - **Regulatory Approval:** Bitcoin ETFs operate under the regulatory framework of traditional financial markets. This provides a level of oversight and investor protection that is often lacking in direct cryptocurrency investments. Regulatory approval can enhance investor confidence and attract institutional capital.

3. **Risk Mitigation:**

   - **Diversification:** Bitcoin ETFs can offer investors exposure to the price movements of Bitcoin without the need to hold the actual cryptocurrency. This allows for diversification within a traditional investment portfolio, helping to spread risk across different asset classes.
   - **Custody Solutions:** ETF providers typically employ secure custody solutions for holding the underlying Bitcoin, addressing concerns related to theft, hacking, or loss of private keys.

4. **Liquidity:**

   - **Market Liquidity:** ETFs are traded on established stock exchanges, providing high liquidity compared to some cryptocurrency exchanges. This liquidity can be especially beneficial for large institutional investors looking to buy or sell significant amounts of Bitcoin without causing substantial price slippage.

5. **Transparent Valuation:**

   - **Net Asset Value (NAV):** Bitcoin ETFs regularly disclose their Net Asset Value (NAV), providing investors with transparency regarding the fund's underlying value. This can help investors make informed decisions based on the fund's performance and market conditions.

6. **Tax Efficiency:**

   - **Tax Treatment:** Investing in Bitcoin ETFs can offer tax advantages compared to direct cryptocurrency investments. Capital gains taxes may be more straightforward, and investors may benefit from the tax efficiency associated with traditional investment structures.

7. **Market Integration:**

   - **Integration with Traditional Markets:** Bitcoin ETFs bridge the gap between the cryptocurrency market and traditional financial markets. As they become more integrated, the correlation between Bitcoin and traditional assets may evolve, potentially offering new opportunities for risk management and portfolio optimization.

8. **Institutional Adoption:**

   - **Attracting Institutional Investors:** The regulatory framework, transparency, and risk mitigation features of Bitcoin ETFs make them more appealing to institutional investors. As institutional participation in the cryptocurrency market increases, it can contribute to greater market stability and acceptance.

While Bitcoin ETFs offer various benefits, it's essential for investors to carefully evaluate the specific ETF structure, fees, and regulatory environment before making investment decisions. As with any investment, there are risks involved, and market conditions can impact performance.

Explore the Benefits of Bitcoin ETFs

Troye Sivan has so many bangers it's ridiculous. I heard this song on the radio and that chorus been stuck in my head since.

Troye Sivan - Got Me Started

Aptos, a Layer 1 blockchain backed by a16z and FTX has just launched.According to the Coindesk article, <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.coindesk.com/tech/2022/10/18/ftx-a16z-backed-aptos-blockchain-off-to-a-rocky-start/">FTX-, A16z-Backed Aptos Blockchain Is Off to a Sluggish Start</a>, "Transaction speeds and tokenomics disappoint on the first day of transactions for the ‘Solana killer’ chain run by ex-Meta employees. Can this protocol gain the trust of investors?"Bullish thread: <a target="_blank" rel="noopener noreferrer nofollow" href="https://twitter.com/macnbtc/status/1581171618298048512">https://twitter.com/macnbtc/status/1581171618298048512</a>Bearish thread: <a target="_blank" rel="noopener noreferrer nofollow" href="https://twitter.com/ParadigmEng420/status/1582121408548651009">https://twitter.com/ParadigmEng420/status/1582121408548651009</a>What do you think?

Aptos Layer 1 Blockchain Thread

Google enters new cryptocurrency partnership with Coinbase

<a target="_blank" rel="noopener noreferrer nofollow" href="https://threadreaderapp.com/thread/1566427754450395137.html">https://threadreaderapp.com/thread/1566427754450395137.html</a>

100 Web3 Startups (by @mishadavinci)

Can AI Ever Understand How Humans Think? - YouTube

What I believe to be one of the most underrated features of LLMs is the ability to convert imprecise human text into code.

In the past, writing a computer program required writing code - aka writing text in a very specific, tedious way such that it can be understood by a computer. A single erroneous character will crash an entire program. Writing code is difficult and tedious enough that it is a professional career that tends to require some degree of study (eg. 4 year CS degree, coding bootcamp), and the job can command annual compensation packages from $100k-$1m+/yr.

LLMs for the first time enable writing programs through natural language, ie. without writing code.

What this will do is make it dramatically easier to create computer programs. The technological jump is the equivalent of trying to talk to someone in Icelandic in 1989 (assuming you don't speak Icelandic), and then suddenly being given access to a modern smartphone with Google Translate.

Some implications:

- Anyone will be able to easily create or update computer programs
- Computer programs will easily be able to create computer programs
- Coding for the first time in history will just be done by regular human language instructions that any non-technical person can write. A disgruntled customer or product manager will simply be able to create a bug report or feature request, and an AI agent will immediately be able to take that and update the codebase (eg. submitting a pull request after testing and code reviewing its own work)
- Programming languages will become unimportant, because any language will easily be able to be translated into any other
- Coding will be commoditized

The human programmer is the translation layer between the human and the machine, and AI is automating that work away, just like it's automating human language translators.

*AI skeptic: So what? Who cares if some geeks can make computer programs easier?*

AI and automation are computer programs!

**AI is making it easier to improve AI.**

This is a feedback loop that results in exponential growth of AI. The more AI improves, the more AI is able to improve itself. Eventually this feedback loop gets so out of control that humans cannot keep up, a point known as the "singularity".

Humans are terrible at comprehending exponential growth, and thus I believe are drastically underestimating how quickly this is all developing.

Most seem to think that the job market for most people is going to be fine over the next decade - I vehemently disagree. I believe that AI will dramatically change society over the next few years and make the workforce drastically more competitive as AI starts to outstrip human ability. The labor market will become so competitive that UBI will become inevitable (I've been saying this for a decade, but never before has it looked so obvious and imminent).

The nature of work will move to a higher level of abstraction. Workers will become more like managers who delegate the "grunt work" to AI - responsible less for the nitty gritty of implementation and building tedious things, and responsible more for deciding what to build and where to direct the AI agents' focus. Just like fast mental math skills hasn't really been a competitive advantage since the invention of the calculator, doing any sort of repetitive, automatable work will not be of any advantage because the AI will be able to do it faster and cheaper at a speed of gigabytes/s, while being able to self-correct and debug itself. As tech becomes commoditized, humans will have to focus more on the "human" aspect such as marketing and zero sum games to economically compete.

The mistake that people who dismiss this tend to make is that they often believe that AGI is required for this mass societal transformation. I disagree. All it takes is for computer programs to be able to make the creation of computer programs easier to achieve this AI flywheel effect.

Anyways just some random thoughts here at 2:11am in Seoul.

LLMs create an Exponential Flywheel for AI Advancement

HN: <https://news.ycombinator.com/item?id=37345727>

Everything I wish I knew before moving 50,000 lines of code to React Server Components

Wavacity – a FOSS port of Audacity to the web

BlackRock to Offer Crypto for Institutional Investors Through Coinbase Prime

"Amazon CEO Andy Jassy has a message to employees who don’t want to return to the office: “It’s not going to work out for you.” That’s according to [a report from *Insider*](https://www.businessinsider.com/amazon-andy-jassy-rto-office-policy-employee-jobs-2023-8), which says Jassy made that statement during a meeting earlier this month.

While [Amazon ordered its employees to return to the office](https://www.theverge.com/2023/2/17/23604485/amazon-return-to-office-three-days-a-week) for three days per week starting in May, many Amazon employees weren’t happy about the decision. [Thousands of workers signed a petition](https://www.businessinsider.com/amazon-hr-chief-rejects-petition-against-return-to-office-policy-2023-3) against the mandate and [staged a walkout in response](https://www.cnbc.com/2023/05/31/amazon-workers-plan-to-walk-out-over-lack-of-trust-in-leadership.html)."

Amazon CEO reportedly told remote employees: ‘It’s probably not going to work out’

HN: <https://news.ycombinator.com/item?id=37301991>

WebLLM: Llama2 in the Browser

66% of Americans want European-style vacation policies, like being OOO for the entire month of August

It's clear that we're approaching the singularity, & most are drastically underestimating the impact that AI will have on society within the next couple years. Some predictions:

\- Humans will not be writing code by hand in a few years.

\- Workers will be expected to move "up the stack" of abstraction. Software engineers will be expected to be more high level product manager hybrids, serving more as technical business managers who delegate low level tasks to AI agents + cheap offshore workers

\- Rise in generalists. Expensive specialists are most at risk since AI democratizes knowledge + power

\- Gutting of the middle class, since most peoples' jobs are now very easy to automate

\- Rise in AI agents. Most of what you read online including on internet forums and in DMs, you won't be able to tell if it was written by a human or AI (already the case with recruiting). There is currently an arms race in AI agent development, the results of which we'll start seeing on society within the next 12 months.

\- The glory days of working in tech are over. Just like very other industry, it's only going to get more and more competitive. Salaries will at best remain stagnant. This is not specific to tech and will be the case for every industry. The industries most resilient will be those that require a human (eg. physical therapy)

The winners will be those who harness AI to their advantage, the losers will be everyone else.

I think most people are drastically underestimating the enormous impact that AI will have on society within even just the next 12 months. People are treating AI like a temporary fad or bubble, as if things will just return to the way they were before. But AI is not only here to stay, it's just getting started, and it's an arms race because everyone knows that AI will eat everything. Humans are terrible at understanding exponential growth, and most cannot comprehend how fast things are about to change.

Not trying to make this political - but I don't see any easier method of alleviating the hemorrhaging of the middle class than governments implementing a Universal Basic Income (UBI). Humans just cannot compete with a superintelligent autonomous AI that has parsed every book and document on the internet. We can continue to be in denial of this while our citizens suffer and overdose suicide to cope with the depression and bleak opportunities, or we can embrace AI and leverage it to free people to spend their time at their own leisure, moving society collectively up Maslow's Hierarchy of Needs. But given how blind and reactionary most people are to this kind of stuff, I don't predict anything changes until we reach a serious boiling point, so unfortunately billions will needlessly suffer in the meantime until the masses wake up to the cosmic societal shifts that are taking place as we speak.

<https://twitter.com/jeremybernier/status/1695350480388714605>

Implications of Approaching the Singularity

<a target="_blank" rel="noopener noreferrer nofollow" href="https://app.santiment.net/charts?settings=%7B%22slug%22%3A%22ethereum%22%2C%22ticker%22%3A%22ETH%22%2C%22from%22%3A%222021-07-27T07%3A00%3A00.000Z%22%2C%22to%22%3A%222022-07-28T06%3A59%3A59.999Z%22%7D&amp;widgets=%5B%7B%22widget%22%3A%22ChartWidget%22%2C%22wm%22%3A%5B%22price_usd%22%2C%22daily_active_addresses%22%5D%2C%22wax%22%3A%5B0%2C1%5D%2C%22wc%22%3A%5B%22%2326C953%22%2C%22%23FFAD4D%22%5D%2C%22ws%22%3A%7B%220%22%3A%7B%22interval%22%3A%221h%22%2C%22node%22%3A%22area%22%7D%7D%7D%5D">https://app.santiment.net/charts?settings=%7B%22slug%22%3A%22ethereum%22%2C%22ticker%22%3A%22ETH%22%2C%22from%22%3A%222021-07-27T07%3A00%3A00.000Z%22%2C%22to%22%3A%222022-07-28T06%3A59%3A59.999Z%22%7D&amp;widgets=%5B%7B%22widget%22%3A%22ChartWidget%22%2C%22wm%22%3A%5B%22price_usd%22%2C%22daily_active_addresses%22%5D%2C%22wax%22%3A%5B0%2C1%5D%2C%22wc%22%3A%5B%22%2326C953%22%2C%22%23FFAD4D%22%5D%2C%22ws%22%3A%7B%220%22%3A%7B%22interval%22%3A%221h%22%2C%22node%22%3A%22area%22%7D%7D%7D%5D</a>