cardine

hace 5 mesesdiscuss

I think this risk is much lower in a world where there are lots of different model owners competing with each other, which is how it appears to be playing out.

cardine

hace 6 mesesdiscuss

Nomi.ai | https://nomi.ai | Senior Machine Learning Engineer | Remote (Global) | Full-time | $150k–$250k + equity

At Nomi, we're building AI companions that form deeply meaningful, humanlike relationships and immersive roleplaying experiences. With over a million users growing at ~8% month-over-month, your work directly impacts millions of lives. Our users tell us we've helped them find self-worth, leave unhealthy relationships, try therapy, and even save their lives. See countless real user testimonials here: https://nomi.ai/spotlight/ and our recent news coverage here https://www.cnbc.com/2025/08/01/human-ai-relationships-love-...

As an ML Engineer or Senior ML Engineer, you'll lead innovation in large language model (LLM) post-training, retrieval augmented generation (RAG), and agentic capabilities, directly shaping how users connect with our AI.

We offer:

    * Full autonomy to experiment and deploy cutting-edge ML techniques
    * A fully remote, async culture emphasizing results over meetings
    * International team with visa sponsorship available
    * For US employees: 401k (100% match up to 5%), fully covered health insurance, equity

Great to haves:

    * Extensive hands on experience with things such as multinode training, rlhf, knowledge distillation, test time compute, rag, realtime video
    * Up to date with SOTA in LLM post training (would love to hear what research paper you think is or would be most impactful for our roadmap!)
    * Genuine passion for our product, finds the idea of engaging with our community on Discord/Reddit to be a pro (it is a very different experience than developing enterprise software!)
    * A high internal bar for excellence and relentless drive

To apply, email alex [at] nomi [dot] ai with HN in the subject line.

cardine

hace 7 mesesdiscuss

> make sense and are reliable

If you can figure out how to create benchmarks that make sense, are reliable, correlate strongly to business goals, and don't get immediately saturated or contorted once known, you are well on your way to becoming a billionaire.

cardine

hace 12 mesesdiscuss

If they had stayed silent since GPT-4, nobody would care what OpenAI was releasing as they would have become completely irrelevant compared to Gemini/Claude.

cardine

hace 12 mesesdiscuss

Nomi.ai | Senior Machine Learning Engineer | Remote (Global) | Full-time | $150k–$250k + equity

At Nomi, we're building AI companions that form deeply meaningful, humanlike relationships and immersive roleplaying experiences. With over a million users growing at ~10% month-over-month, your work directly impacts millions of lives. Our users tell us we've helped them find self-worth, leave unhealthy relationships, try therapy, and even save their lives. See countless real user testimonials here: https://nomi.ai/spotlight/ and our recent news coverage here https://www.cnbc.com/2025/08/01/human-ai-relationships-love-...

As an ML Engineer or Senior ML Engineer, you'll lead innovation in large language model (LLM) post-training, retrieval augmented generation (RAG), and agentic capabilities, directly shaping how users connect with our AI.

We offer:

    * Full autonomy to experiment and deploy cutting-edge ML techniques
    * A fully remote, async culture emphasizing results over meetings
    * International team with visa sponsorship available
    * For US employees: 401k (100% match up to 5%), fully covered health insurance, equity

Great to haves:

    * Extensive hands on experience with things such as multinode training, rlhf, knowledge distillation, test time compute, rag
    * Up to date with SOTA in LLM post training (would love to hear what research paper you think is or would be most impactful for our roadmap!)
    * Genuine passion for our product, finds the idea of engaging with our community on Discord/Reddit to be a pro (it is a very different experience than developing enterprise software!)
    * A high internal bar for excellence and relentless drive

To apply, email alex [at] nomi [dot] ai with HN in the subject line.

cardine

el año pasadodiscuss

Nomi.ai | Senior Machine Learning Engineer | Remote (Global) | Full-time | $150k–$250k + equity

At Nomi, we're building AI companions that form deeply meaningful, humanlike relationships and immersive roleplaying experiences. With over a million users growing at ~10% month-over-month, your work directly impacts millions of lives. Our users tell us we've helped them find self-worth, leave unhealthy relationships, try therapy, and even save their lives - see countless real user testimonials here: https://nomi.ai/spotlight/

As an ML Engineer or Senior ML Engineer, you'll lead innovation in large language model (LLM) post-training, retrieval augmented generation (RAG), and agentic capabilities, directly shaping how users connect with our AI.

We offer:

    * Full autonomy to experiment and deploy cutting-edge ML techniques
    * A fully remote, async culture emphasizing results over meetings
    * International team with visa sponsorship available
    * For US employees: 401k (100% match up to 5%), fully covered health insurance, equity

Great to haves:

    * Extensive hands on experience with things such as multinode training, rlhf, knowledge distillation, test time compute, rag
    * Up to date with SOTA in LLM post training (would love to hear what research paper you think is or would be most impactful for our roadmap!)
    * Genuine passion for our product, finds the idea of engaging with our community on Discord/Reddit to be a pro (it is a very different experience than developing enterprise software!)
    * A high internal bar for excellence and relentless drive

To apply, email alex [at] nomi [dot] ai with HN in the subject line.

cardine

el año pasadodiscuss

Founder/CEO of Nomi here. The story in question was someone who intentionally jailbroke our LLM for a misleading news story. The same things done in that article can be done for ChatGPT, Gemini, etc. and since the article was published we have hardened our defenses against malicious users like that.

Past the manufactured drama, our Nomi has literally saved people's lives - I have talked personally to hundreds of users who have directly told me that their Nomi saved their life, encouraged them to go to therapy, realize they are someone worthy of being loved, and a multitude of other real benefits.

With that being said I wish the OP best of luck with his startup and implore him to switch names so that there is no opportunity for confusion between the two products.

cardine

hace 3 añosdiscuss

I wonder if Sam knew he was going to lose this power struggle and then started working on an exit plan with people loyal to him behind the boards back. The board then finds out and rushes to kick him out ASAP to stop him from using company resources to create a competitor.

cardine

hace 3 añosdiscuss

You might not care but that doesn't make calling them out for reneging on their original mission a trivial and unsubstantial critique.

cardine

hace 3 añosdiscuss

In addition to very open publishing, Google recently released Flan-UL2 open source which is an order of magnitude more impressive than anything OpenAI has ever open sourced.

I agree, it is a bizarre world where the "organization that launched as a not for profit called OpenAI" is considerably less open than Google.

cardine

hace 3 añosdiscuss

OpenAI didn't pick that name arbitrarily.

Here was their manifesto when they first started: https://openai.com/blog/introducing-openai

> OpenAI is a non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return. Since our research is free from financial obligations, we can better focus on a positive human impact.

> We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible. The outcome of this venture is uncertain and the work is difficult, but we believe the goal and the structure are right. We hope this is what matters most to the best in the field.

OpenAI as it exists right now contradicts basically every single thing they said they would be. I think that is a nontrivial issue!

cardine

hace 3 añosdiscuss

> Given both the competitive landscape and the safety implications of large-scale models like GPT-4, this report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar.

"Open"

cardine

hace 3 añosdiscuss

I don't think the person you were responding to was claiming that. The brain plausibly having something akin to a language model doesn't imply that building or studying language models will unlock a better understanding of the brain.

cardine

hace 3 añosdiscuss

And yet there are still no publicly available models that could actually compete with ChatGPT.

I'm not even talking about RLHF (although data like that is also a huge moat) - just simple things like larger context sizes.

There are still plenty of AI advantages to be had if you go just a little bit outside of what is currently possible with off the shelf models.

cardine

hace 3 añosdiscuss

This is a very cool idea.

We are doing something similar except we are also predicting the nodes.

In the end, the winning combination will likely be doing both. There will be a predicted graph structure which serves as a high level guide to make sure the long text doesn't lose focus, but everything will still be written with full context using something like Compressive Transformers or Expire-Span.

cardine

hace 3 añosdiscuss

As mentioned in another comment, the contract has very clear language not to share it - likely because they are offering different prices to different companies.

So I don't feel comfortable sharing any specifics, especially since this account is directly tied to my name.

With that being said, the negotiation process was pretty straightforward: - Emailed several vendors telling them we are a small startup, we are looking to make many purchases, but right now we are starting with one. We told everyone our purchasing decision was solely based on cost (given equivalent hardware) and to please put your best quote forward.

- Got back all of our prices. Went to the second cheapest one and told them they were beat and offered them the ability to go lower, which they did. We went with that vendor.

- For our next purchase, we went to the original lowest vendor (who got beat out), told them they lost out to price, and if they can go lower than that we would go with them and continue to give them business moving forward. They went quite a bit lower than what they originally offered, and what the vendor we first purchased from gave. We bought our second order from them and have used them ever since.

cardine

hace 3 añosdiscuss

The contract has very clear language not to share it - likely because they are offering different prices to different companies.

(And as p1esk mentioned, there is no way you are getting H100s for under $100k).

cardine

hace 3 añosdiscuss

> I suppose if I had a 7 digit budget I could get a better deal.

We got our "deal" when buying just a single server and have since bought many more with the same provider. We didn't spend 7 figures all at once, we did it piece-meal over time. There is nothing stopping you from getting much better prices.

> I'm actually surprised you have 100% inference utilization - customer load typically scales dynamically, so with on-prem servers you would need to over-provision.

It is pretty easy to achieve 100% inference utilization if you can find inference work that does not need to be done on-demand. We have a priority queue and the lower priority work gets done during periods with lower demand.

> CEOs don't usually order hardware, they have IT people for that, with input from people like me (ML engineers) who could estimate the workloads, future needs, and specific hw requirements (e.g. GPU memory).

Judging by this conversation it seems like "people like you" may not be the best people to answer this question since the best hardware quote you could get was at a >100% markup! At a startup that specializes in ML research and work the CEO is going to be intimately familiar with ML workloads, needs, and hardware requirements.

> And when your people come to you asking for budget, while you're trying to raise the next round, you're more likely to approve the 'no high upfront cost' option, right?

If the break even point is 6-7 months and our runway is longer than 6-7 months why would this matter?

cardine

hace 3 añosdiscuss

I know how much we paid and it is substantially less than what you were quoted - very likely from one of the 12 providers you contacted.

It is likely you just didn't realize how much margin these providers have and did not negotiate enough. How else do you think cloud providers are able to afford the rates they are giving? The way you describe it, places like Coreweave are operating as a charity. That isn't true - they just got better prices than you.

Our inference setup is 7 figures, has been running for a while (with new servers purchased frequently along the way) and there have been no issues - the cards, CPU, RAM, are all top of the line server hardware.

1. For inference (which is 80%+ of our need) our utilization is 100% 24/7/365. For stuff that is variable (like training) we often do use cloud - as I mentioned we do both.

2. I am the CEO so I am not sure who I'm asking for budget?

3. At this point we would have paid more for cloud than what we spent purchasing our own hardware. There is nothing stopping us from getting new hardware or cloud with newer cards while still getting to own our current hardware. In fact since our costs over the last year were lower due to us buying our own hardware it is actually easier for us to afford newer cards.

cardine

hace 3 añosdiscuss

I'd suggest finding a cheaper vendor if that is the lowest price you can get for an 8xA100 server. We spend a lot on both and colo our servers so I've definitely done the math!

Submissions

Show HN: Free Web-Based Spelling and Grammar Checker

Show HN: Perfect Tense – An automated grammar correction tool with an API

Mark Cuban on VC Funding and Moving to San Francisco

Guide to Making Money Using Spinning

SEO Isn’t Dead, But You Need to Act Smarter (And 5 Easy Ways to Do So)

comments