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Layvier

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Gemini 2.5 Flash 1 year ago

Agreed, it's not even possible to run an eval dataset. If someone from google see this please at least increase the burst rate limit

We were using gpt-4o for our chat agent, and after some experiments I think we'll move to flash 2.0. Faster, cheaper and a bit more reliable even. I also experimented with the experimental thinking version, and there a single node architecture seemed to work well enough (instead of multiple specialised sub agents nodes). It did better than deepseek actually. Now I'm waiting for the official release before spending more time on it.

"It's time for OpenAI to return to the open-source, safety-focused force for good it once was," Musk said in the press release. "We will make sure that happens.""

From the creator of Grok, this is such an insane thing to say

Retro on Viberary 3 years ago

you would probably first tag the papers (AI papers then being tagged with "AI"),then generate for instance an Elasticsearch query with an LLM for matching papers with the ai tag and the word transformer

Retro on Viberary 3 years ago

Yes I had a look at it, I haven't tried e5-mistral-7b-instruct yet but I'll definitely give it a go. Is there such a leaderboard only focused on retrieval by any chance? I haven't found one so far

Retro on Viberary 3 years ago

This is a problem we're hitting as well. Hyde (Hypothetical Document Embeddings) is a zero-shot approach to it, where from the query you generate documents that would have a very small distance to the actual documents you're looking for. For question answering this would mean generating hypothetical answers. In some cases though, it can yield better results to generate hypothetical queries for each documents, question answering actually being one of them. That requires a lot of pre-processing though, which is not always possible.

Retro on Viberary 3 years ago

I'd be curious to hear what people think is state of the art of this kind of problem? I think the Cohere embeddings model v3 is very good, as it handles queries and documents differently to embed them in the same vector space. Otherwise for a specific use case I guess dense retrieval (which is basically a problem specific fine tuned version of this approach) is the best way to go about it?

TelescopeAI | Remote - European timezones | Full-time - AI Engineer (NLP, LangChain, Weaviate)

At TelescopeAI (https://gotelescope.ai/), we are building a product that is going to revolutionise (and we mean it) the sales industry forever, positively impacting millions of people, companies and products.

Our platform uses advanced machine learning to perform prospecting on autopilot, and can identify the right customer for the right company at the right time.

We have incredible backers in Sequoia Capital and Entrepreneur First who are partnering with us on our ambitious mission.

We are building a team of superstars to undertake this legendary journey with us. You can drop us your application at contact [at] gotelescope [dot] ai.

TelescopeAI | Remote - GMT+-2 | Full-time - Fullstack Software Engineer (Typescript/React/GraphQl) - AI Engineer (NLP, LangChain, Weaviate) - Founding Product Designer

At TelescopeAI (https://gotelescope.ai/), we are building a product that is going to revolutionise (and we mean it) the sales industry forever, positively impacting millions of people, companies and products.

Our platform uses advanced machine learning to perform prospecting on autopilot, and can identify the right customer for the right company at the right time.

We have incredible backers in Sequoia Capital and Entrepreneur First who are partnering with us on our ambitious mission.

We are building a team of superstars to undertake this legendary journey with us. You can drop us your application at contact [at] gotelescope [dot] ai

So I'm pretty new to Terraform, and in my team we were planning to set it up for our infrastructure next month. Does that change something for us? If it stays backward compatible I assume not much would have to be done for switching? I'd definitely prefer an open license.

Telescope | Remote - GMT+-2 | Full-time

- Fullstack Software Engineer (Typescript/React/GraphQl): https://gotelescope.notion.site/Full-Stack-Engineer-61f17de7...

- Machine Learning Engineer: https://gotelescope.notion.site/Machine-Learning-Engineer-04...

- Designer (no job ad yet, but please apply: we're looking for a stellar product/UI/UX designer to be our first full-time designer)

At Telescope (https://gotelescope.ai/), we are building a product that is going to revolutionise (and we mean it) the sales industry forever, positively impacting millions of people, companies and products.

Our platform uses advanced machine learning to perform prospecting on autopilot, and can identify the right customer for the right company at the right time.

We have incredible backers in *Sequoia Capital* and *Entrepreneur First* who are partnering with us on our ambitious mission.

Having been chosen to the inaugural *Sequoia Arc program* in Europe from amongst 3000+ startups just further validates our belief that we are on to something truly remarkable.

We are building a team of superstars to undertake this legendary journey with us.

I get where this comes from, but at least in France and Germany it's not questioned that there will be assistance and even direct intervention from the gouvernement on the electricity market. We're talking about democracies with strong socialist components after all. And also, Macron will definitely do everything to avoid another Yellow Jackets episode...

Meh, it's not gonna be the end of the world. Prices for consumers will increase (maybe around 3x), but if the poorest are helped accordingly it's not so bad and will actual push people to be more responsible. This whole crisis actually mostly show how absurd our energy grid is, and the poor strategic choices made in the previous decades. It also pushes for much needed reforms and investments (300 billions in renewables announced a few days ago).