jdnier

Wait, so this object is going to pass quite close to Jupiter, Mars, and Venus? And the Juno probe, which was planned to be decommissioned soon anyway, could potentially be maneuvered to follow and get close to the object? Kind of uncanny and kind of a science fiction plot, but fun to think about.

Hi, just wondering what you're thinking about how your tool might be abused.

An overview of other studies investigating cysteine and glycine sources and effects (from 2023; video or transcript):

https://nutritionfacts.org/hnta-video/how-to-get-less-cystei...

LLMs trained on LLM generated material trained on ... until just gray goo is left.

So I wonder how much of Claude's perceived personality is due to the system prompt versus the underlying LLM and training. Could you layer a "Claude mode"—like a vim/emacs mode—on ChatGPT or some other LLM by using a similar prompt?

Make sure the check out the LLM chat log he shared for the current article! The tone is cynical HN commenter indeed.

https://github.com/minimaxir/llm-use/blob/main/criticism_hn....

> Alright! We managed to plot two sine waves in the most convoluted method ever!

Those sine waves start to resemble a multi-voice music score. You might get some interesting pitch variability depending on other processes that are running.

The author is Co-founder of Databricks, creator of K Prize, so an early adopter.

Interesting article relating Adam Unikowsky asking for Claude to decide a Supreme Court case: https://blog.plover.com/tech/gpt/presidential-emoji.html

"Claude is fully capable of acting as a Supreme Court Justice right now."

See "Rye and Uv: August Is Harvest Season for Python Packaging"[1]

[1] https://lucumr.pocoo.org/2024/8/21/harvest-season/

Are you able to describe what makes them better? (Honest question, I'm not familiar with either or with Amphi.)

It seems Definite's use case is focused on connecting to lots of data sources. For much smaller scale, how does Amphi compare?

Wow, django-ninja is just what I was looking for. Thanks for pointing it out. Here’s their CRUD example: https://django-ninja.dev/tutorial/other/crud/

Thanks for pointing this out. I had never really thought much about it. I 100% agree with you! The docs are totally why Python is so comfortable for me.

Vega-Altair seems to have some introductory documentation and a tutorial for their flavor.

https://vega.github.io/vega/docs/

Is their a Python-centric tutorial or guide on how to construct plots in this grammar of graphics way? Or do you need to read the ggplot2 book and translate R examples to Python?

From the forward:

> This is an excellent report which argues that the cephalopod molluscs and decapod crustaceans should be included in the UK animal welfare law in an explicit way, based on a detailed and important scientific and philosophical framework and evaluation, coupled with extremely helpful suggestions for improving best practice and welfare, and for regulating existing practices that currently raise widespread concerns about the welfare of these animals.

The first link is about The China Study. Here's the Wikipedia description, if you're not familiar with it:

https://en.wikipedia.org/wiki/China%E2%80%93Cornell%E2%80%93...

> The China–Cornell–Oxford Project, short for the "China-Oxford-Cornell Study on Dietary, Lifestyle and Disease Mortality Characteristics in 65 Rural Chinese Counties," was a large observational study conducted throughout the 1980s in rural China, a partnership between Cornell University, the University of Oxford, and the government of China.[1] The study compared the health consequences of diets rich in animal-based foods to diets rich in plant-based foods among people who were genetically similar. In May 1990, The New York Times termed the study "the Grand Prix of epidemiology".

Cancer as well. See The China Study (https://nutritionstudies.org/the-china-study/). See also this summary of other research studies here: https://nutritionstudies.org/12-frightening-facts-milk/

Whoa, they're almost all using capital letters.

From the abstract:

  Here, we present Codon, a domain-extensible compiler and DSL framework for high-performance DSLs with Python’s syntax and semantics. Codon builds on previous work on ahead-of-time type checking and compilation of Python programs and leverages a novel intermediate representation to easily incorporate domain-specific optimizations and analyses.

Same phone transition for me. I keep saying "typing on my phone is the most disappointing part about living in the future." (Ok, so no flying cars yet, I can handle that, but texting on my phone is embarrassingly awful, considering phones in general are so far beyond what anyone imagined they'd be like in the 70s.)

His repo is here: https://github.com/dmagliola/regex_game_of_life

It's like the Hubble Deep Field only with a lot of obvious gravitational lensing.

Yep, the first image just dropped: https://www.nasa.gov/image-feature/goddard/2022/nasa-s-webb-...

Here's podcast interview with the creator of jq about what he's been working on at Jane Street: https://signalsandthreads.com/memory-management/

Here Quanta's editor-in-chief explains his thoughts on a print version [2018]: https://www.publishersweekly.com/pw/by-topic/columns-and-blo...

That's largely what their excellent Signals & Threads podcast is about.

https://signalsandthreads.com/

> Listen in on Jane Street’s Ron Minsky as he has conversations with engineers working on everything from clock synchronization to reliable multicast, build systems to reconfigurable hardware. Get a peek at how Jane Street approaches problems, and how those ideas relate to tech more broadly.

No one's commented yet, but wow, I had no idea. This is a fascinating read, and very accessible.

Thanks, I had never run across Streamlit, which looks very mature. I'll try out Plost.

A good video walkthrough of Textual from September, 2021 with Paul Everitt interviewing the author, Will McGugan: A Look At – and Inside – Textual (https://www.youtube.com/watch?v=1kTWxamIJ_k).