How long we will be testing and benchmarking generative capabilities of LLMs? in creativity, in code generation less or more result is expected and approved, but in execution $19.8 can not be $19.9 or $19.7.
This is something i have been looking for long time, however i have gone through repository and docs and the problem is bigger and solution still seems to be early, I am curious how you gonna take further, will be watching it
The article is great reflection how LLMs are actually doing Quality assurance on both security and codebase sides, but i still doubt the creative part that means UI side, So far in my experience LLMs at best are unable to determine what the good UI is , may be its not inherently a bug detection rather a creative process
One of the core issue here is LLMs are probabilistic not deterministic, even with set of rules or context , llms are inherently built to make best guess, so my question is how you are ensuring that LLMs are following rules?
Answers are there ! that was the whole point of my question, using or not using should be Personal choice not government Ban , everything on internet has pros and cons.
That is the exact thing , I asked that because its primary a personal choice, and I support EU regulator decision on it, If you need VPN for usage like keeping your personal information intact its perfect but if someone else is using for other purpose then again it should personal choice rather than government regulation ( this might not sound good to some).
I agree with your point of view we need more research papers specially Breakthroughs AI is acheiving must be published and verified with sound mathematical backings, At our startup we are also moving in this direction perhaps I have already onboarded an Applied Math Phd from Germany to help me in researching.
I am wondering how they are even allowed to run such experiments? it is not only the business case, its pure security breach and specially given the magnitude of data they hold or power AI posses, I think all must be immediately stopped and till OpenAI comes with complete clearance nothing should be allowed
Actually this debate highlights how big the AI war is! my personal opinion is LLMs must be opensource and borderless, and ofcourse with given reputation i will use USA based Opensource model than the chinese one, but will they release opensource alternatives that is the question that will be answered in future
Went through the Readme, the direction you point out is exciting but i still wonder what it communicates? would love to know your personal opinion what you try to accomplish here?
I agree with you, instead of working on creating a bash script if we just sit as a senior developer ,check and correct what is needed is the way forward, it kind a remind me Pair programming when one do the scripting and other corrects it
Being a vivid reader , I usually want to read at an speed of the interest I have in subject, for example I love history, so i read it slowly but for tech kind of book i love to read faster and grab whatever i want to from that book, I believe if you cover both of those points mentioned ( UI Correction and speed per book) then it would look more tailored version
The pace of LLM improvement is insane, but this also opens a door that if the data is organized perfectly and right set of mathematical rules are set , this whole phenomenon of machine learning can open doors of new dimension that humanity might never have thought before, there is still much to explore in space in oceans and even in the way work on our very planet, sky isnt the limit anymore.
The whole article is very well summarized in these two lines :American leadership requires two things: world-leading American open-weight models and continued access for U.S. builders to open models already available worldwide, and I beleive Not only US but Europe and all around the Globe we should have same pursuit.
The business use case of rather than going on one model choosing the best openweight model and reducing the cost seems fascinating, however the context memory, or auditability of what is happening behind would be more complicated, even within single model we have to spend tons of time to decode and understand llm behavior , add context layers and so on, having said that for GenAI executions this might be the direction. Wish you best for the project
Though the core of the product seems to be younger enough and also i couldnt find a link to github for more detailed query but the direction about database should do more and it should evolve as per needs of Agentic Era seems to be fascinated and I am already working on that direction from my end too, Wish you best for this project.
The idea looks cool , i think along with optimization reading time if it also allows you set your frequency and then read the book accordingly it would really make an impact , for i sometimes want to read slowly if the topic is of my interest. Just a suggestion