This guy’s like Jack Black meets Nicholas Hoult.

This was a really nice interview and interesting project. It’s incredible the superpowers that we developers have gained over the last two years. Things that you could’ve asked for 10 years ago and I would’ve said maybe with a year and a few million dollars worth of headcount are now an API call away. I have LLM‘s integrated into nearly every part of my workflow and my tooling. The way I work now looks almost nothing like the way it used to. I want to know more about the price difference with Gemini flash versus Whisper for transcription particularly with all the many flavors of local whisper that are available. I’ll have to do some research on this.

Fantastic tool and fun examples that actually demonstrate fun little use cases.

Is there a place where one could explore all the published datasettes?

kzbin.info/www/bejne/eYLFnJuPnJd3sK8si=bBBGXe5F6RoeMtS_

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Amazing work Simon! Thank you!

Can i use this Plugin along with MySQL .. getting errors.

Thank you, very informative

Thank you for sharing.

Thank you Simon Wilson. Great information. I especially like how you demonstrated the development of your own tools. Finally my thoughts is your presentation in an executive summary format will educate policy makers in both the enterprise and government sector who seem to have fear of AI. For example my company has an existing early policy that employees are not allowed to use AI or ChatGPT. At the same time my Use Case to leverage RAG was to augment our LLM was accepted by our AI Review Committee. My thought is the enterprise companies will be careful and prudent in the rollout of LLMs and AI tools because they will want “security rails” in place. Thank you.

Thank you .

Mask, in 2023...

I just took a poll. And people said if you could show us OSINT using a model like mistral that is mostly uncensored (Dolphin/Instruct) or whatever your preference is then gpt4. Everyone who responded agreed that would be something we would pay for. 2024 tips and tricks LLMs and OSINT. But there are advantages to uncensored.

This is the best fundamental way of describing embeddings.

This is what microsoft recall wants to do

This man is truly based.

this is really nice! thanks for sharing.

I’m totally new to embeddings and this video inspired me to want learn even more!

I've recently stumbled across your work which I read about in Gergely's book "Software Engineering Guidebook". Fantastic find. Love the creativity here.

Love this! Would be useful to mention you need to run datasette in --root mode in order to make modifications, it took me a while to find this.

Is it possible to replace the OpenAI API key with local vision model instead?

there should be some kind of authorized base restriction on internal llm tokens to normal public

very great demo, thanks for sharing! this is an excellent example of practical use of embeddings.

Thanks for linking yourself on ycombinator, very interesting talk and quite engaging delivery.

The future is wild. Imagine how good this will be 6 months or a year from now.

New to Datasette. Just installed it on OSX with Homebrew, and added the Extract plugin, but I'm not seeing the 'database actions' button. Am I missing something?

🔥

Nice

That's fantastic. Does it work across multiple websites and in different languages? For example, if you wanted to provide a list of specific events in a country where both English and Spanish or Italian are spoken but have a single database in English.

Awesome!

Thanks very interesting and useful.

Things start to become magical.

This was so good! Please do more of these - i am still in awe!! Thank you!

"vibes-based search" lol. love the term you invented.

Cool

Impressive fast talking and fast scrolling. A lot of knowledge and experience for sure. I guess I'll have to do some digging if I want to really benefit from this lecture.

Why are you wearing a mask 😷?

What a genius

Looks great, but setting it up is not easy... I have installed plugins, created a config file for the API key, and started Datasette, but nothing ever changes. A setup video for Windows or Linux demonstrating how to set up plugins would be appreciated!

Very cool! thanks for sharing

Synthetic data 😁

OMG, the pause button got a workout. Cheers!

How does the semantic vectorization of a word look like, in a mathematical sense ? Is it like every word has it’s spatial ID (coordinate) and gets kind of multiplied with a vector array of assoziatives IDs?

Great talk. Very interesting subject.