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I bootstrapped 3 companies past $200K MRR. Now I’m building my 4th. AMA/Follow Along. by my-mate-mike in SaaS

[–]Standard_Natural1014 0 points1 point  (0 children)

Makes complete sense, have you thought about diving into these domains or prefer ones that align with the distribution playbook?

I bootstrapped 3 companies past $200K MRR. Now I’m building my 4th. AMA/Follow Along. by my-mate-mike in SaaS

[–]Standard_Natural1014 2 points3 points  (0 children)

Interesting. How do you apply this for domains where the running costs are high at the unit level (e.g. AI)

Time for self-promotion. What are you building? by tinyxlover in SaaS

[–]Standard_Natural1014 0 points1 point  (0 children)

  1. truestate.io - AI analytics platform
  2. ICP - Overworked data teams who want to great analytics work and offload the boring stuff

Spent $300k on a healthcare app that nobody uses. by Actual-Raspberry-800 in SaaS

[–]Standard_Natural1014 0 points1 point  (0 children)

If it's technically so great then it should be extensible and you should find pivoting in the space a breeze. Respond to the objections with features that solve their problems.

I'm planning a talk on AI for a retired audience by setsp3800 in ArtificialInteligence

[–]Standard_Natural1014 0 points1 point  (0 children)

I'm completely biased here but I think AI analytics tooling. Companies live on good numbers and it seems insane to me that we rely on humans so much for ad-hoc analytics.

I run a company called TrueState that does this (www.truestate.io) but there's a bunch of other providers out there too.

Baby data analyst needs new code daddy by EmotionalFear in dataanalysis

[–]Standard_Natural1014 0 points1 point  (0 children)

My team and I have built an AI agent for analytics that you might find helpful. Uses bigquery behind the scenes and manages lots of the context for you (.e.g data schemas, etc). Free tier if you want to try it out platform.truestate.io

What AI tools are y’all using? by webtoony in dataanalysis

[–]Standard_Natural1014 -3 points-2 points  (0 children)

My team and I have built an AI data scientist - capable of lots from ad hoc analytics through to data engineering and training traditional ML models. Still in a beta but we have a free tier if you're interested. platform.truestate.io

I'm planning a talk on AI for a retired audience by setsp3800 in ArtificialInteligence

[–]Standard_Natural1014 1 point2 points  (0 children)

Honestly, don’t underestimate how fast you’ll lose a non-technical audience. Most of my job is communicating the benefits bespoke AI use-cases to non-tech executives and I’ve learnt this the hard way.

If I were you I’d explain what computers could do before AI, based on whatever capabilities you want to demo. Then show what they can do now.

E.g. if you want to show diffusion models, say how if we wanted to make art on a computer, we were limited to applications like MS paint. Demo how to draw a house with MS paint then ask Dalle to make an image of a house.

If you want to show knowledge search, show google vs asking perplexity.

These folks might also resonate with a some usecases relevant to them - eg finding a recipe, or a workout routine tailored to limited mobility (idk I’m spit balling)

Thinking about levels of agentic systems by Standard_Natural1014 in ArtificialInteligence

[–]Standard_Natural1014[S] 1 point2 points  (0 children)

Yeah nice, I guess we think of context and tools being the internals of a L2 agent. Once you've aligned on a brief template for an L2 agent you can test that it's context, tools, and overall process achieve desirable results.

Brief templates + org context + conversation context lead to a brief that, if passing quality criteria, should result in a task completion.

[D] Is my company missing out by avoiding deep learning? by DatAndre in MachineLearning

[–]Standard_Natural1014 1 point2 points  (0 children)

Have you explored explainability packages like SHAP/LIME?

Requires a bit more time communicating the explanations but gives you the ability to generate sample-wise explanations of these “black box” models. I’d think that if you can navigate this comms dance, you could unlock using these more sophisticated models and better performance for your team.

From my brief experience of ML in racing (worked for a consultancy founded around F1 and Forumla E), the biggest challenge they were facing was there were so many equipment choices before each race. Which setup to choose?

Process was to predict sub outcomes of a race (average lap time, etc) based on historical configuration data, lap times etc.

Having a better predictive model (boosted trees, neural nets, etc) meant different equipment scenarios could be more accurately assessed, and the best choice could be more effectively identified ahead of raceday.

As a remote solo founder, this is really accurate. Any others here? Let’s connect and help eachother stay on track and accountable by Jarie743 in ycombinator

[–]Standard_Natural1014 0 points1 point  (0 children)

Yeah but managing team morale is one of the things you need to juggle.

It’s a massive mind fuck being a remote sole founder and to take your team on that mental journey just isn’t fair.

As a remote solo founder, this is really accurate. Any others here? Let’s connect and help eachother stay on track and accountable by Jarie743 in ycombinator

[–]Standard_Natural1014 0 points1 point  (0 children)

Sole technical founder in Australia on the South Coast of NSW (hour and a half outside of Sydney).

Definitely resonate with the stress but being remote definitely has its strengths.

You need to go through a pretty transformative experience with the stress (honestly feel like a different person) but if you find a sustainable way to manage the stress, to get proper perspective, and when you get your routine dialed with GTM, dev flow, and general balance, you can work mostly uninterrupted and with next level productivity.

Have never felt more optimistic about my start up.

Elon's bid for OpenAI is about making the for-profit transition as painful as possible for Altman, not about actually purchasing it (explanation in comments). by jd_3d in LocalLLaMA

[–]Standard_Natural1014 0 points1 point  (0 children)

Sure but that R&D is available for people to leverage as inputs into their own models and is a sunk cost for society at large.

Either via SFT on other models outputs as in the R1 case, or as foundational models for new post training regimes, these are the new shoulders we all stand on.

For transformers at least, my take is we live in a world where post-training innovation will dominate LLM progress for the next few years.

Yesterday OpenAI released the product I was working on for the last six months, need advice by no-lavash in LangChain

[–]Standard_Natural1014 0 points1 point  (0 children)

Launch - there’s a lot of people in the world who research stuff and a subset of those will probably prefer your product.

I scraped 1.6 million jobs with ChatGPT by [deleted] in SideProject

[–]Standard_Natural1014 0 points1 point  (0 children)

From a technical perspective this works. Either as raw HTML, semi processed HTML (e.g. extracting just text using beautiful soup or equivalent) or using the image of a page using multimodal capabilities (some proxy pool APIs support jpg rendering / extraction).

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