tmountain

It’s optimistic to assume that a Democrat will be permitted to hold the office of the President. It came down to Mike Pence last time, and things have changed a lot since then.

You might argue it is illegal.

Thanks, that's helpful!

What makes for an amazing cable? For USB, if it carries data and power, I’m usually pretty happy with it.

This all sounds good, but the Government of one of the world's primary super powers (The United States) is currently unwilling to participate in fighting climate change, so any plan seems DOA without a major policy change on that front.

Used to be? Isn’t this still the case?

Different people with different motivations.

There are lots of ways to have a fully functional brain besides writing code manually…

I think the rapid improvements in local models will make a $2,000/mo price point completely impossible to sustain. This feels like a race to the bottom.

Slop style.

Yup, I think the author needs to take their own advice and invest some time into putting it into their own words.

Yup, it’s a great UX and it makes the media experience feel finished, not hacky.

As a musician, I can agree with this 100%.

Cause all the kids are hooked on crack.

Floppy disks were ubiquitous when I was in college. When I got into Linux, I did an experiment raw writing zeros to floppies with dd to see what percentage of them had I/O errors. I tested with a stack of about 50 of them that were left in our computer lab over the years (different brands). The failure rate was staggering. Something like 30-40% of them had bad sectors. After that, I realized that I could never rely on them as a storage medium for anything important without regular backups.

We could probably debate this ad nauseam, so I'll just give you my most compelling arguments.

1) Writing code the "old fashioned" way (i.e., a Python program that does X, Y, Z) allows you to arrive at a battle tested solution that will not change over time. From a risk assessment perspective, the behavior is essentially immutable, allowing a business to guarantee consistent behavior over long periods of time.

2) Just because something hasn't happened to you do, does not mean that it will not happen. LLM are opaque. If you stay on the "happy path", you may see consistent behavior for long periods of time, but there's always potential for an edge case where something goes catastrophically wrong. This is without even opening the can of worms regarding prompt injection and intentional sabotage of a working system.

3) There are plenty of real world examples of an LLM spontaneously deleting data from a DB (or the entire DB) or otherwise going completely off the rails. These might seem hyperbolic, but it happened at our company (to a test DB, not production). The severity of errors that occur can be existential to a business' survival without the proper guard rails.

4) There's no concrete way to truly confirm understanding between an LLM and a human. It can tell you that it completely understands what you want, and then it can do exactly the opposite. Followed by, "my bad" (Claude's new favorite catch phrase). Code can be audited and even proven to be correct given the appropriate level of time and energy.

My best results have been gleaned in using LLM to produce deterministic systems. I recognize everyone has different use cases and needs, but this seems to be the best use of the technology in my experience.

The craziest for me is companies that sticking stochastic agents into automated business processes and expecting stable/reliable outcomes. Businesses want deterministic processes in the vast majority of cases.

It’s been wildly successful. Poorly run projects tend to fail.

Someone has to look out for the big guys! /s

Lots of people have solar. Green AI, imagine that!

There are plenty of honest millionaires, but no honest billionaires.

I have been working on a language learning app for myself, and I am using a textbook that I like as the basis for an Anki inspired “learning tree”. This is working pretty well because I can build progressions from the original table of contents.

Context here (Patrick Boyle):

https://youtu.be/IHD8BDFYyGI?is=dnpBeOoxH7LUJknm

A huge chunk of SoaceX value in their filing is attributed to their AI technology (aka Grok). I believe it’s 90% or more… Now, it seems they’re leasing the infrastructure required for Grok to scale to Anthropic and Google. I wonder how that math works…

Yeah, but then it’s either an arduous manual review or incurring a bunch of token usage to review something that may be slop.

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We build AI-assisted auditory training for people with hearing loss. Our product is live, in clinics, and growing internationally.

Backend Engineer: Postgres-heavy work on Supabase: PL/pgSQL functions, pgmq queues, Deno edge functions, billing and cron systems. You like databases enough to enjoy writing triggers and RLS policies, and you want to own systems end-to-end rather than just ship tickets.

QA Specialist: Manual testing of our iOS/Android app and web tools, working alongside our head of QA on a clinical product where data quality, platform stability, and accessibility are critical to our mission.

Note: Candidates must be in time zones no further west than EST; Western Europe is fine.

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Big dreamers, which is awesome, but they need a disciplined PM type team member to bring them down to Earth (ROI analysis on their roadmap).

I tend to agree, but the gains will come at the expense of the early adopters. Then again, this has been the case in so many industries throughout history.

For a preview of how this will go, take a look at this:

https://accounting.penrose.com/

Got it, thanks.