Scaling people by Claire Hughes Johnson is a recent one that is quite good.
Readit Newscicce19 commented on Ask HN: What are the best articles on managing people? · Posted by u/deadcoder0904
Not sure if this exists, but as a remote/distributed startup with no physical office, i use my home address on contracts and for mail. I'd like a service (in Canada) to allow me to register my address somewhere, ideally a commercial location, and forward all my mail to my home address or my partner's home address if addressed to him.
this is running on custom hardware, if you’re curious about the underlying architecture check the publication below.
https://groq.com/wp-content/uploads/2023/05/GroqISCAPaper202...
EDIT: i work at Groq, but i’m commenting in a personal capacity.
happy to answer clarifying questions or forward them along to folks who can :)
Will you be selling individual cards? Are you looking for use cases in the healthcare vertical (noticed its not on your current list)? Working in the medical imaging space and could use this tech as part of the offering. Reach out at 16bit.ai
cicce19 commented on Do large language models need all those layers? amazon.science/blog/do-la... · Posted by u/belter
I was a RSNA this year (major Radiology conference and trade show) and one of the presenters made the claim that their model was generalized because it works on different body parts. My intuition was they were claiming they trained it on one body parts and it subsequently worked on different body parts (which could be convincing). So at first this seemed fine. But in reality they had trained the same model on all of those body parts. That really go me to thinking about the old myth that we only use 10% of our brains. Anyway I think capacity would be when the model can no longer learn.
But anyway it made me wonder if there's a way to measure "what x% of a model is actually used" similar to the myths about human brains.
I was also at RSNA. What was the model intended to do in this example?
Furthermore, what is stopping Google/Alphabet from exercising their IP rights (i.e. They own a patent for the transformer architecture)? Sure it would be bad publicity, but it seems like they could prevent a ton of competition by simply enforcing that on a few large competitors.
cicce19 commented on French AI startup Mistral secures €2B valuation ft.com/content/ea29ddf8-9... · Posted by u/admp
Does anyone know the advantage of mistral over llama2? I understand the founders of mistral previously worked on llama.
cicce19 commented on Large Language Models Are Zero-Shot Time Series Forecasters arxiv.org/abs/2310.07820... · Posted by u/Anon84
> They are a brain addition machine
I like that metaphor. LLMs are masters of linguistic addition. They are literally made by adding up language gradients. They accumulate knowledge and insight through exposure to vast swaths of text, stitching together concepts and ideas into an ever-growing tapestry of understanding.
But whereas brains are isolated islands, unable to directly share their contents, language forms a collective reservoir that flows between minds. Words and ideas mix and mingle within this pool, combining into new formulations that reflect the present.
In this way, language displays an evolutionary dynamism that outpaces biological change. LLMs ride this wave, leveraging the emergent intelligence inherent in humanity's shared linguistic legacy. The wisdom accumulated over generations surpasses the capacity of any single mind. We stand upon the shoulders of giants, supported by the communal scaffolding of language and knowledge that previous generations erected. LLMs tap into this source, channeling and distilling the experience contained within our words.
tl;dr AI is riding the language exponential while we are distracted by models and brains, implementation details.
This is a really elegantly worded perspective
I've noticed lately that I have a lot of jaw tension which is linked to stress and I think information overload which is related to this article. Has anyone else had this? What has worked?
This is good for Radiologists and not so good for orthopedic surgeons.