itissid

Noob Question: There is a famous parlor trick with generative networks(I think it was GANs but it might be some kind of diffusion based network.), you start with a canvas and draw a stick figure of what you want and the generative network draws the rest of it.

Do AI platform companies actually pre-train networks to do the same for hand drawn artists?

Related question: If they do train them to do that, are there any that train people for the "reverse": learn how to draw with paper and pencil by showing techniques only i.e only the "what" but not the "how" ?

Ah so you extract decisions, actions and outcomes and you index and search over them?

Especially for indie users/devs and smaller teams. I built a part of this(the retriever) in < 4 hours https://github.com/itissid/wiki for replacing deepwiki.

I think the challenge is to teach how ranking works to people more effectively so that they can build it for themselves and host them on their own.

Like the other day someone who has worked in search explained to me why you would care about using learning-to-rank(LTR) technique to train your own feature vector weights on your data. My understanding is that weighted features work better(retreival wise) on textual data than plain BM-25 and vector embedding db indexing of text chunks of your data with minimal preprocessing. So if you have lots of conversations you can create a ton of features(like attributes of a conversation) from it and ones that matter more will rank higher. And you can use a regularization(like L1) to kill unimportant ones.

[EDIT]: IIUC, I think LTR is important because you likely want different features to matter more for different parts of your documents, e.g. what matters for codebase documentation is different from your personal journal.

I have a request: can this text be even more AI generated?

I think the main reason for this outrage is partly a confluence of factors some of which you pointed it.

But my money/theory is on what I call `alonliness` specifically due to lack of labor mobility: There is no good rapid transport connecting american interior towns to big cities and people don't want to move due to a variety of factors(real estate debt, cultural affinity to area). To be clear these people are alone but not necessary lonely(there is that going on too in other segments of the population). And once you don't understand or never had the opportunity to understand something(or rather only experience its bad side effects), you distrust it at best and fear and hate it at the worst.

If you ask people 1:1 IRL who live in communities where the main source of employment is not whatever Silicon valley businesses are. They will ask you questions or make comments like " 'those' jobs are not real American jobs!" or "Aren't you afraid of getting thrown on subway tracks in NYC?". These are actual questions i got from people there.

These give an indication of the disjointedness of the sets in the venn-diagram of of the socio-economic equality and what creates such psyche. I am not sure why some think its a PR/Comms problem for big tech.

Interesting. Making low latency correct tool calls correctly is pretty important in voice AI cascading models(STT LLM TTS). Realtime Models are still 2x the cost and there are only 2 providers openai and google that are in the race. For cost control it has to be cascading models

For llms Sadly the only model right now that fits the bill for LLM is GPT 4.1 and it’s standard in my stack because thinking models have unacceptable latency(>=1 sec) even though they are good at tool calling. The main issue with 4.1 is that it can make still mistakes and prompt prose has to be tuned quite a bit.

I wonder if any local models can be tuned to match the response time and tool calling while supporting many languages.

Still too narrow a take on what self help techniques are killable by ai. I also think self help as a bunch of life hacks and habits is precisely what’s wrong with the industry writ large. They are based on what sells in a capitalist system targeting the attention economy. Creating scarcity on supply side of attention(work longer) and demand side(addictive apps). Take Atomic Habits, one of the things it says is out of many is making the habit you want to form easy to do, e.g place sneakers and shorts next to your bed to make a habit to run in the morning. It presumes a lot about how exactly habits are actually internalized, retained and how one falls into or out of them. I’ve fallen in and out of such habits even after I did them for a while(months). Techniques are very ripe to disruption because people don’t quite understand or have time to understand or observe their own mental state, so hacks sell because you can do them(presumably) as a monkey would.

It’s not an electronic problem but an human first IRL interface problem. A shining example to the contrary is meditation practice like Vipassana. Saying you can kill that with AI is like saying “Gandalf is here and he explained to you the meaning of life and said now you don’t have to live or learn lessons anymore because you know I can always ask him”. Of course living the actual life is the whole point! It’s also why IRL experiences like classes and communities tend to work better when structured as lived experiences.

If this industry of self help books dies I won’t shed too many tears.

#TIL multiple myeloma went from being a death sentence in the 90's to quite manageable using a really old compound called thalidomide[1]. Though it sad that it was exploited for almost two decades to line the pockets of a dozen rich a*holes.

[1](https://www.propublica.org/podcast/revlimid-cancer-drugs-fda...)

I wonder if the government might consider reversing the circadian cycle and tell people to work in the night and sleep in the day. At this point its better because IIUC many animal's reproductive system shuts down at such high temperatures.

And I would not discount this govt considering it given that far less rational, crazier, things have happened in the past like for instance randomly cancelling high denomination cash notes.

Yep and the speaker is not half bad! It has good hardware. Its a shame they could not spin it off to anyone else(not for lack of trying) before they were "forced" to kill it because, basically, meta's stock was at 90$ at the end of 2022 and everyone was just spewing a derivative of the statement: "Focus on extremely short term profitability else your(heavily) stock compensated employees will all leave."

I've heard there is a way to know if your resume is getting blackholed by a AI resume screening process — sort of like a test to fix it up. Any one knows how that works?

https://archive.ph/YwAky

People generally limit the number of roofs to one, as they are expensive and important for keeping the outside out and the inside in.

What does this mean?

And why is it the worst place to put solar panels? Is this and America only phenomenon, cause in India people are installing them like hot cakes on the roof. What’s different about roofs here?

Has anyone gone back to doing code katas, code craft like exercises by hand? They help keep me grounded.

Also I feel like it’s fine to let AI write your code. I felt very much like the OP did. A couple of things help keep my sanity. one is that as developers I think our job has evolved to knowing what decision an AI makes is good and which one is bad, this can be code or design – but there is nowhere a developer(or for that matter a knowledge worker) can hide from ai. In this world you will be forced to communicate with them. Partly because as a community we have decided(for better or worst) that AI should bring non trivial amounts of productivity gains to software development.

The other one is something I want to validate which is for those of us who are mediocre at coding, it might be a gift because it would free up some time and thus mind space to consider what we are actually good at.

There is no difference between claude -p and typing into their "harness" in tmux. They want to make you pay for API which is subsidizing these plans.

They say they want to do it due to their percieved misuse(via automation) of `claude -p`, this I find laughable because they can always rate limit based on how fast a human types/STT's into a text box. Heck, they could provide TUI based extensions(something you vibe code in a few days today) to get better observability and DX for harness use, I would not mind using `claude` CLI directly, but they wont.

Forcing people to using their garbage harness — 0 observability, no extensibility and poor DX — is a showcase of how this fiasco is playing out: They refuse to improve their CLI and want to push everyone to use their API with multiple poorly rolled out policies.

I did too. did you do this mainly for observability reasons and a better harness?

So ive been using claude -p from last year with a harness around it called codelayer(i am sure some of you have been using something similar too). Their harness is completely garbage when it comes at displaying full details of tool calls and session management. A example is how pressing ctrl-o does not display any detail of messages above the scroll bar buffer. It also flashes and rescrolls like bonkers.

The codelayer harness is great at exposing to me thinking tools and tool calls by scrolling and clicking and expanding it. I can scroll and click into any tool call and search the entire session with / less style even if the string is buried in a subagent or tool call. Entire session timeline are visible on the right if I need to navigate to a user/assistant message. None of this is in the default harness.

I would say its naive to regulate the algorithm than its effects. The effects are all that matter at the end.

Instead, a regulation could mandate the administration an anonymized unbiased mandatory eval test at the end of every week/bi-week/month just like instruments for psych evaluation (e.g. do you feel your <mental-health-metric> has become worst in the last <time-period> on <scale>. Did you have <mental-health-marker> after watching content on social media?).

The said regulation can then mandate that after calibration and correction the feed pull back by training the algorithm to adjust it in a rapid A/B test.

This is all doable by the companies themselves, but since they wont, the key is to mandate it and publish the aggregate results regularly — like make it part of the quarterly share holder's SEC reporting requirement or something.

He did mention in one of the planet earth 2/3 series how so much of the land is used for farmed animals. And, for the sake of completeness of argument, for restoring what was lost, the challenge is how to raise the standard of living fast enough for people so they give a damn about anything apart from ourselves was THE challenge to combat climate change and global ecological disaster. He specifically mentioned e.g. educating girls and making older-aged societies more propsperous. Prosperous people can make better choices about farmed animals as food.

You do know that in china while renewables are 30-40% of installed capacity(how many GWh they can theoretically produce), they are a smaller portion of generated capacity because if inefficiency of grid, intermittency if sun and wind. They are a smaller ~9-10% of Total Energy consumed (which is much bigger pie including for e.g. gas cars, jet fuel, diesel etc), right?

They may be able to distribute all solar panels and wind turbines worldwide; in the end that is just tiny-potatoes good because those markets are not that big. But when it comes to getting to energy independence they are using an "all of the above" strategy to get there. Planetary catastrophy can take a back seat to socio-economic unrest due to less/no money and opportunities for people.

Also how EMs in amazon construct hunger games. Just hire a person every now and then so they can let go of another to prove you made your team better on some non-sensical performance evaluation axes..Cue the hunger games.

Wonderful. ultrasonic range emission having high S/N is amazing too. My hero usecase for this is to use these for behavioral therapy: Have a ring or a bracelet, thus without reaching for a phone or a notepad, record when a negative thought happens, i.e. a counter, or generate a sequence of ultrasonic sounds to map to specific kinds of thoughts. Have a sensor record and log them. I would then analyze the data across multiple days. My current method is recording them in obsidian.

But, in context learning could be better. One important thing here also is the ability to align on what to more/less pay attention to — no matter the Knowledge Base. These are the highest leverage points that need to be exposed to a human to think and reason over. Constrained/Guardrailed development tasks work fine*, But exploration new direction — vs exploiting local minimas — is still an achiles-heel, even with all these knowledge unless there is sufficient steering and exploration the minima-seeking "tries" hard to win.

* With Claude's 1-million context window I have been doing some slightly longer range tasks — ~1-3 days of work — with RPI/QRSPI frameworks(see last few days of comments else where on HN) in one context window. They involve a grill-me session with 20-60 sometimes more questions for tasks to get alignment which produces the design and the plan in one window.

No duplicate the whole task e.g. I use grill-me skill for planning and it takes me ~3 hours and CC asks me 20-40 questions. Do the same grill-me with this and compare the outcomes. I admit Its quite a lot of work to duplicate, but i am really itching to do this over a few tasks and compare the final plan. Just need the time.

So RPI/QRSPI like skills (e.g. https://github.com/mattpocock/skills and https://github.com/humanlayer/humanlayer/tree/main/.claude/c... and https://github.com/dfrysinger/qrspi-plus ) for working with claude code work well enough for me that they can reliably* produce code that matches the plan/spec in a way they did not till December 2025.

I have a gut feeling that these models can do just as well, has someone run a reasonable size task — >=1-2 days of designing and planning — and see it work well with these models?

* For me what worked well was the grill me skill(or its variation) at the design stage, the hygiene I followed here was have it ask one question at a time, resolving dependencies at the design stage and reading the hashed out plan closely. The use of a couple of other MCP tools like a documentation server like deepwiki and arxiv for grounding. Other tricks I use are having high signal tests and having claude either be able to read logs and code at the same time or embedding it in the execution(e.g. as a debugger, repl or devtools)

Interesting. How do you yourself use this(I am assuming of course you built it out of a need to want to have to track this data)?

Has someone found that they have better alcohol "recovery" if they are pursuing intense or at least regular(at least 3x a week) stamina building exercise like running/swimming?

As someone said we live in a strange but amazing era, where although it has never been easier to be deceived, but its _also_ much easier to uncover said deception especially on the internet.

For course correction, I began with trying to think a bit more about solving problems for my clients by talking to them more often. That helps to some extent because I feel happy talking to them for understanding how to solve their problems.

What I do feel the issue is with I just having to do everything to keep costs down because hiring another dev vs doing it with AI consideration is real and it has collateral damage: I spend more time trying to build AI agents to do the work and there is 1 or 2 fewer jobs I create.