How do I access AlphaEvolve?

Not something I would do at any point for fun. But anecdotally, it's materially better than other alternatives offered/available.

Colnomic and nvidia models are great for embedding images and MUVERA can transform those to 1D vectors.

  - additional modalities
  - Faster FPS (inferences per second)
  - Reaction time tuning (latency vs quality tradeoff) for visual and audio inputs/outputs
  - built-in planning modules in the architecture (think premotor frontal lobe)
  - time awareness during inference (towards an always inferring / always learning architecture)

Have you checked out dataset building with nemotron? The nemotron synthetic data builder is quite powerful.

Moreso, check out model merging. It's possible if you merge some of your model against llama3.1 base it may perform much better.

Check out max labonne's work on hugging face

https://huggingface.co/aaditya/Llama3-OpenBioLLM-70B

In the roadmap is adding video export, digital twin presentations, and real-time presentations. We don't wrap a public LLM, so we don't share any data.

We’re Nick and Roman. We’re solutions engineers who spend a lot of time prepping for and delivering product presentations and demos. We realized that we were spending too much time tailoring scripts for our client presentations and sales demos, practicing our pitch and (sometimes) nailing our delivery.

So we built pitchpilot to save time customizing the pitch and adding the right voice to it. You can also download and share your presentation in no time.

We hope this tool will be as useful for you as it is for us. Let us know what you (don’t) like and how you use it for work, fun, etc.

Cheers, Team pitchpilot

Comments URL: https://news.ycombinator.com/item?id=40986256

Points: 1

# Comments: 1

[1] -- https://www.biorxiv.org/content/10.1101/2022.11.18.517004v3

1. First, models will predict pollution. The outcomes will help shape urban policy. But these won't solve crime or stop people from driving.

2. Second, models will predict individual behavior and track person level emissions. The outcomes will force behavior changes, mostly freedom limiting.

3. Third, and finally, models will predict thoughts. The the thought of driving instead of walking might trigger a response.

It's a slippery slope and we need to draw a line between prediction and policy.

https://cdn.swisscows.com/image?url=https%3A%2F%2Fi.pinimg.c...

Only question, why do you name variables with the λ symbol?

Despite all the bad press, shady exchanges, bubbles and busts, a large amount of BTC owners don't sell, and that alone will drive it's price up. Other cryptos, I can't speak for.

The NSA is very good at math, so I'm be thoroughly surprised if this analysis was error by mistake rather than error through intent.

1. You should really download the huggingface hosted model.

2. Why convert the model if meta already hosts it here: https://huggingface.co/meta-llama

3. This step completely glossed over the hardware requirements. Doesn't explain any of the instructions needed in the finetuning process.

4. "Now run the model". What? What about the model precision, hosting, standard open source tools, etc,etc...