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Rami's Readings #19
The latest on AI anxiety and predictions, LLMs in the medical field, Passkeys, world trade data, WEF’s Future of Jobs report, and more.
Welcome to Rami’s Readings #19 - a weekly digest of interesting articles, videos, Twitter threads from my various sources across the Internet. Expect a list of reads covering technology, business, culture, fashion, travel and more. Learn about what I do at ramisayar.com/about.
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Many things happened this week; First Republic got acquired by JPMorgan Chase, King Charles was crowned, and an article about moats around AI/LLMs was leaked (no comment, see disclosure in #7). The following are other notable reads from the week, and do not miss the Future of Jobs Report:
🤖 AI Reads
Notes: Tyler Cowen spot on again. If you had to read one article this week, this is it.
I do not hear much engagement with the economic arguments that, while labor market transitions are costly, freeing up labor has been one of the major modes of material progress throughout history. The US economy has a remarkable degree of automation already, not just from AI, and currently stands at full employment. If need be, the government could extend social protections to workers in transition rather than halt labor-saving innovations.
So I will declare mine: decentralized social systems are fairly robust; the world has survived some major technological upheavals in the past; national rivalries will always be with us (thus the need to outrace China); and intellectuals can too easily talk themselves into pending doom. All of this leads me to the belief that the best way to create safety is by building and addressing problems along the way, sometimes even in a hurried fashion, rather than by having abstract discussions on the internet. So I am relatively sympathetic to AI progress. I am skeptical of arguments that, if applied consistently, also would have hobbled the development of the printing press or electricity.
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Notes: Short under 5 pages paper.
Notes: LLaMA continues to be consequential overall. In this case, fine-tuning on medical data showed an improvement on medical tasks.
Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness
Notes: Great news!
Notes: This hack is mitigated by turning on Face ID, but it is still disappointing there isn’t an additional check on the device before setting a recovery key. I suspect Apple will fix this soon given the media coverage.
Notes: Supply Chain Cybersecurity is critical.
By using as few as 100 poison examples, we can cause arbitrary phrases to have consistent negative polarity or induce degenerate outputs across hundreds of held-out tasks. Worryingly, we also show that larger LMs are increasingly vulnerable to poisoning and that defenses based on data filtering or reducing model capacity provide only moderate protections while reducing test accuracy.
💼 Business Reads
Notes: In my opinion, the big winner in the short-term will be Mexico.
Notes: Great insight in this report. Machine Learning and AI specialists have a promising future, as do general IT professionals.
Notes: If you need an example of the impact of the Twitter blue check saga on the rest of the world, here is one. Ugh…
Notes: I use Firefox frequently, but this read is concerning.
That is all for this week. Signing off from Victrola Coffee, Seattle.
I wrote a disclosure for this newsletter in #7. Please consider reading it.
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