Sounds nice except that these are 1 very small scale model, 1 reranker, and 1 embedding model that are far from frontier LLM level. And they're not open sourced.
As much as I agree with the message, this reads like marketing copy trying to make a big deal out of a tiny model being hosted privately.
Just talk to them as if they were already your friend. Most of what you talk about with friends isn't just mutual interests and you start conversations with them all the time.
This blog post describes the basic work of a research engineer and nothing more. The amount of surprise the author has seems to suggest they haven't really worked in ML for very long.
Honestly? This is the best its ever been. Getting stuff to run before huggingface and uv and docker containers with cuda was way worse. Even with full open-source, go try to run a 3+ years old model and codebase. The field just moves very fast.
The paper you're talking about is "Deal or No Deal? End-to-End Learning for Negotiation Dialogues" and it was just AIs drifting away from English. The crazy news article was from Forbes with the title "AI invents its own language so Facebook had to shut it down!" before they changed it after backlash.
> the generation of 281,128 augmented examples, from which 1,000 were
held out as a benchmark test set.
This model is trained on a custom dataset of 280k examples then tested on 1k very similar examples from the same dataset. Of course it is specialized to outperform general models on this specific task in this specific domain with this specific json format for output.
This is a reasonable hobby project and interesting approach to synthetic data generation but not impressive research.
At minimum you should test your model on other benchmarks that have similar tasks e.g. docbench
I think it's pretty obvious it's 1. Given the recent huge, clearly politically-motivated cuts from the current administration, it feels pretty likely that FOIA could be disrupted under the guise of "cost-saving".
And I think you're supposed to be generous to the commenter, not the current administration ;)
> IR temperature sensor for checking your body temperature or stuff you baking in the oven
> tiny thermal camera sensor for inspecting leaks in house for the winter
So just a thermometer gun? It costs like $20-30 on amazon and I've never needed one other than in my home / kitchen. Why in the world do you want a phone for this haha.
Good summary of some of the main "theoretical" criticism of LLMs but I feel that it's a bit dated and ignores the recent trend of iterative post-training, especially with human feedback. Major chatbots are no doubt being iteratively refined on the feedback from users i.e. interaction feedback, RLHF, RLAIF. So ChatGPT could fall within the sort of "enactive" perspective on language and definitely goes beyond the issues of static datasets and data completeness.
Sidenote: the authors make a mistake when citing Wittgenstein to find similarity between humans and LLMs. Language modelling on a static dataset is mostly not a language game (see Bender and Koller's section on distributional semantics and caveats on learning meaning from "control codes")
You understand some of what your cats mean because you learned it using the same language games Wittgenstein describes. Also they co-evolved to work with us. But just because you understand three moods of your cat, doesn't mean you would understand their language (if they had one). In fact, it is well studied that cats communicate differently with other cats than with humans.
Sidenote: grouping together non-verbal communication and language fails to take into account the richness of language.
The problem with your perspective is you are assuming children have independent wants and needs to work and can stand up for themselves like adult workers can. This just isn't the case.
Children don't personally decide to work, they are told to by parents / authority / etc.. and they are incredibly vulnerable as employees. Comparing child labour to lemonade stands is ridiculous. There are rules about children working in the family store etc.. and child labour laws explicitly account for this. Child labour laws are explicitly about preventing abusive conditions in factories, fields, and other hard, grueling jobs.
> The solvents we need in this case are the healthier methods of fulfilling these longings.
Terrible take. Algorithmic feeds and ad-tech has continually optimized how to get and maintain our attention. It is ridiculous to think "going into nature" or any individual solution is the answer. We blame pharmaceutical companies for making addictive drugs, why don't we blame tech companies for making addictive apps?
As much as I agree with the message, this reads like marketing copy trying to make a big deal out of a tiny model being hosted privately.