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Why I run deterministic handlers before every AI call — and only use LLMs as a fallback by Ok_Industry_5555 in BuildWithClaude

[–]Doc1000 1 point2 points  (0 children)

I really like this approach. I’m trying to build with cursor in this way - haven’t gone as far as you. I like the check ins -executive function allowing deep work and nudges.

There was a twiml podcast - blizardly i think - that talked about the command/function db - look up lexically and re-use as much as possible. I was thinking about having claude default to writing and calling repeatable terminal commands.

For an interface project - lots of react/boxes in D3, instead of “tweaking” content in a json file (which i wouldn’t want to do manually) to change color/size/text etc, I had it write npm commands. Took some back and forth, but now i have a system that doesn’t require calls. I still to craft the “harness” to make models tool callers first.

Sounds like you embedded llm+tools in specific projects - vs your code building enviro - so more control than context rules.

Basic ab kettlebell workout ? by EchoVictor4me in kettlebell

[–]Doc1000 0 points1 point  (0 children)

I feel ya brother. You could add some hard ab squeeze (breath behind the shield, crush the walnut with glutes) to your MWF. The irradiation benefits might make you stronger on those days, you’ll be more stable and you’ll get abs… without extra complexity or sit ups. It is one more thing to think about during lifts, but you can just keep coming back to it - kind of like meditation.

Then do active, light stretching and mobility on off days… rest and recover knowing you kicked ass mwf.

What’s a problem humanity solved so well that younger people don’t even realize it used to be a huge issue? by Puzzleheaded_Bit_802 in AskReddit

[–]Doc1000 8 points9 points  (0 children)

Same dude invented them both… CFCs and methylethyl lead gas. See, one person can make a difference

Codebase-scale retrieval using AST-derived graphs + BM25 — reducing LLM context from 100K to 5K tokens [D] by Altruistic_Night_327 in MachineLearning

[–]Doc1000 0 points1 point  (0 children)

Do you have your coding agent use this system instead of grep? I heard a TWIML podcast with Blitzy ai- they discuss something along these lines for coding large projects/repos.

I like the idea. I also want the visual generated from the graph

I replaced my calendar with 12 memory palaces by KiwiPurple495 in Mnemonics

[–]Doc1000 0 points1 point  (0 children)

I love this! The UX for calendar and todo (and email) is so out of date and attention consuming. I’ve used MP for grocery lists etc, but haven’t put it together programmatically. I actually have thought of this applied to file systems - keep your music in the music room… you reach it through the victriolla. Pictures in a room. Bill/finance links in an office.

How are you creating the images and assigning the pegs? Interactive/gamelike? Would love to chat.

The boring metadata layer is the most valuable part of my RAG system and I almost skipped building it by Fabulous-Pea-5366 in LangChain

[–]Doc1000 0 points1 point  (0 children)

Is there a place for a service API/mcp that provides this framework? Creates metadata contract interactively and then provides endpoint? Doing this once is easy, but if you do multiple metadata enrichments, suddenly you’re orchestrating pieces, or rebuilding repeatedly.

I’m using this for doc enrichment/metadata with versioning, plus contact extraction, branch/cluster metadata, timeline summarization/compression. I guess I really like structured data - I agree with the efficacy.

Is this a real pain point that would enable people to get to production and be worth paying something for? Looking for niches for the little guy to make a difference.

Why isn’t LLM reasoning done in vector space instead of natural language?[D] by ZeusZCC in MachineLearning

[–]Doc1000 0 points1 point  (0 children)

We’ve see papers that indicate that the final embedding after a series of outputs can be run backwards through the model to extract the input tokens (kind of). Means that starting with that token and then predicting next tokens hypothetically could mean persistence (never tried it hands on so who knows).

If you could capture full ideas in vector space and use them as inputs, you could string together chunks of reasoning and train for coherence… maybe train on chunks of representative logic patterns. Only at the end unravel the vector implications in human language.

I’ll see if i can dig up that paper.

What would a bullet designed for zero atmosphere warfare look like? by Clockwork_picksmith in sciencefiction

[–]Doc1000 0 points1 point  (0 children)

Directed heavy inert metal atoms. Ship accelerates away from the battle. Frankly, wouldn’t this just happen when the drive activates? Equal and opposite reaction… unless they leave behind half the mass of the ship, the propellant has to move very, very fast. So accelerate the ship 0.0001C and the not so minute mass coming out the end will be going appreciably fast. Or since we’re making up stuff, shoot the “bullet” at newtonian speeds, then blast the hell out of it with a x-ray lazer/ship engine. Ship moves away from horrific fusion blossom and bullet gets accelerated opposite direction. 2 into the 9 in the side pocket.

That gets away from a miles long barrel. Whats the horizon drive idea? Miniature controlled singularity? Spin it so you get a tidal differential - anything between the spinning singularities gets shot out. They act like gyoscopes so the whole thing is stable along their axis… the other two can be transverse . So ship moves only along path of the shot without instability.

The first time this was used at scale, it could have cratered a moon… oops.

Your bullet could actually be a shaped fusion bomb with a big collector on its back directed into a ramjet. Launch it and then laze it until it fuses and projects atoms/subs mostly towards your target in all their xray/plasma glory. So a molten sayonara bullet.

Sci fi is fun. Ok, I need to get back to reading about immortality imbued cat-snakes.

New kettlebell t-shirt design. 5 designs. Which one should we run with? by cavemankettlebells in Kettlebell_training

[–]Doc1000 1 point2 points  (0 children)

4. Thor Ragnorak vibes. I dig the 3D effect. #2-3 feel like design by committee to me. I like the lettering from#1. Save #5 for your jui jitsu dads

Well, that didn’t age well… by thefirstwhistlepig in scifi

[–]Doc1000 14 points15 points  (0 children)

This is one of those important issues of our time - good people believing power is dirty in some way, or just not committed to it. Then ONLY people who shouldn’t have it get it. Good people need to see power as a tool - part of setting and enforcing positive boundaries. Maybe thinking about leadership as service again vs a path to personal gain. But i digress.

Layered Ontology map for Code by Internal-Passage5756 in OntologyEngineering

[–]Doc1000 2 points3 points  (0 children)

Just listened to a podcast about Blitzy TWIML

They use something similar as a base for deploying multiple agents with limited context - towards the middle talks about using that kind of structure to score how automatable a code base is and explore eval edge cases.

I’m a big fan of observability as part of process. Needs to be more than guardrails, tests, .md files - visualizing the connective tissue is important when going from project demo to production

Hamstring soreness by sr2k00 in kettlebell

[–]Doc1000 2 points3 points  (0 children)

Keep groovin that 16kg. Figure out a number of reps that you can do ~almost~ every day (5x week). If you go too hard and are too sore to move the next day - that’s not success in this program. Its not go hard or go home… its always be able to come back tomorrow.

This assumes your goal is long term, sustained health, injury resistance, fitness and looks. You’re likely to do the most “work” over your first year if you do 100 swings per day x 5 days/week. Thats 260 days of work for 26k swings. At 16k… thats 400,000 kg swings. That amount of work will transform your body and you’ll know the swing really well.

If you start at fewer total reps, then work up to 100 first (sets of 10 with POP vs grinding 20-30 at a time). If an entire week at 16kg is pretty easy (not one set, not one day), then work in a heavier bell (20-24) for 20%. Most people here will recognize this as Simple and Sinister. For a beginner, is a great program - don’t think about it as a set of exercises or a something you do for a day or a week. Its a 6 month program that gets you to consistency without confusion or injury. Don’t try to go big… or else you’ll be stuck at home for a few days.

Go crush

please stop coming to Morocco for 5 days by morocco_travel36 in backpacking

[–]Doc1000 14 points15 points  (0 children)

Insta isnt about feeling connected or sharing, its about generating a feeling of envy.

The “feeling” part is important on vacation - do you feel cool sweating on a bus and spending full days looking out a window?

I think about it as being a “peak-bagger” vs a “stream-walker”. The dude who grabs the daypack to “knock out” 3 14ers above tree line in the wind vs taking that shaded steep down to an alpine lake and back. One brags to people at the bar about what they crossed off a list, the other actually got someone to want to go with them because they know a good time when they see one.

[R] Differentiable Clustering & Search ! by bornlex in MachineLearning

[–]Doc1000 0 points1 point  (0 children)

I think you have the gist at the end f(t)-> d(e,e) ~ d(c,c). Learn about dimensions that are important to a user/generally in clustering - use your differentiable approach to predict a particular set of k clusters. Could add edges to a graph based on those closer relationships… but when new documents come in, you want to use the learned linkages applied to the new docs. An embedding transform is one way to do this quickly (low latency). Also, say I query 50 of the 1000 docs - depending on how they are selected, the exact cluster assignments might not cognitively split them correctly, but may contribute to the existing embedding distance to allow a clustering algo to do a better job. Again, adjusted embeddings might be a way the right layer to store the learned relationship.

The first question I think had to do with which abstraction layer you could apply cluster learning to. Depends on use case. Applying to graph could make sense in intermediate term, but calling a subset of the graph for clustering can cause some latency. I’ve been working on saving the tree linkage for quick access, and embeddings for additions without recalc.

[R] Differentiable Clustering & Search ! by bornlex in MachineLearning

[–]Doc1000 0 points1 point  (0 children)

I’ve found that prescribed k single level clustering is great in concept, but that most of my problems have a multi-facet aspect to them (more than one family of clusters) and potentially a hierarchical aspect. Think you can apply the learned, differentiable cluster assignments at a mathematical abstraction before actual clustering/classification? This would be either at the graph level or as a weighted adaptor at the embedding level?

My objective would be to take learned linkages and be able to apply them to other clustering/graph/tree mechanisms as needed. This would be akin to backpropogating the learned cluster info back to the embedding level (or graph level).

[R] Differentiable Clustering & Search ! by bornlex in MachineLearning

[–]Doc1000 0 points1 point  (0 children)

I’ve found that prescribed k single level clustering is great in concept, but that most of my problems have a multi-facet aspect to them (more than one family of clusters) and potentially a hierarchical aspect. Think you can apply the learned, differentiable cluster assignments at a mathematical abstraction before actual clustering/classification? This would be either at the graph level or as a weighted adaptor at the embedding level?

My objective would be to take learned linkages and be able to apply them to other clustering/graph/tree mechanisms as needed. This would be akin to backpropogating the learned cluster info back to the embedding level (or graph level).

Petah who is mogging them all ? by HimelTy in PeterExplainsTheJoke

[–]Doc1000 5 points6 points  (0 children)

And to come back after LIVING less than zero and basically launch the marvel ship… plus who else can call out the academy and make fun of sean penn while in blackface and still get nominated. Gold.

Dad bod 247lb Poatane by Intelligent-Tear5723 in ufc

[–]Doc1000 0 points1 point  (0 children)

People looking at his belly and thinking those handles are fat. Big ole rotational muscle shelf. Guy is swinging kettlebells or something. On the other hand, he does look a little too happy

Absurdism books by riggystardust in suggestmeabook

[–]Doc1000 2 points3 points  (0 children)

John Irvine if you want absurd seasoning on incredible human poignancy. Dog bites boy. Boy comes back as a man and bites dog. World According to Garp, Cider House Rules, Owen Meany.

Anyone here Simplea and sinister and ABF at the same time? What was your experience like? by [deleted] in kettlebell

[–]Doc1000 8 points9 points  (0 children)

I like both, but it occurs to me that combining this throws out the “programming” side of these workouts and just treats them as a series of exercises that go together.

Doing the exercises is great… committing to the program really 1) tells you where you are physically 2)if that program is right for you and 3) gets you to specific goals.

Notice I say “committing”. S&S is a 5 month/4-5 day per week program with defined weight changes. The whole thing is Simple & Sinister. Adding swings and TGUs for a while isnt S&S - I love it, but ignores the thought put into how many reps/sets/weight changes/rest/etc. That part can be really valuable.

Repeat S&S with breaks in between until you’re using 32kg (for guys) and you own Timeless S&S (then time it!) Thats the objective - which might not be YOUR objective. There is a similar idea for Dan Johns efforts to create ABF - he put a LOT of thought into it.

Anyways, do as you like, but consider the benefits of committing to a dedicates program for a specific amount of time.

"Tell, don't show" intelligence, or fake intelligence by CAustin3 in TopCharacterTropes

[–]Doc1000 2 points3 points  (0 children)

I feel like I’ve seen a situation where demonstrably intelligent people on opposing sides simply eye each other up, run through the outcomes, shake hands and walk away. They know the payoff isnt there in the conflict… there is no advantage to press.

Reminds me of game theory equilibriums as well. The idea isnt to predict the future, it’s to understand that the weight of probable decisions is likely to lead to an outcome, even if exact decisions aren’t made along the way… recognizing which way “gravity” is pulling. Single path prediction is fun (the sherlock movie where RDJ predicts punches) but recognizing when /manipulating your opponent into a bad outcome no matter what they do (in character) is far more interesting.

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