Cesar Osorio

AI Data Scientist. I help companies create, deploy and monitor machine learning solutions . @GeorgiaTech CS alum - @PyconCa speaker

[Cesar Osorio @cesarosoriof]

@alexocheema @huggingface great presentation, please let me know if i can get early access to https://t.co/apkwXrA0BT thanks!

[freeCodeCamp.org @freeCodeCamp]

Open source LLMs can help you create intelligent apps without having to pay for each API call.

And you can use Mistral AI's open source models to build your own intelligent apps.

This course teaches you how, and you'll code some projects along the way.

https://t.co/6y5e1gEjZa

[Amir Feizpour @amirfzpr]

"I don't want workflows, I want agents"

this is a common thing I started hearing from my commercial clients and bootcamp participants (who probably have read the Anthropic article on this topic - or more likely have seen the title as they were scrolling through social media)
1/n

[elvis @omarsar0]

Practical Recommendations:

Users are better off consolidating all requirements into a single prompt rather than clarifying over multiple turns.

If a conversation goes off-track, starting a new session with a consolidated summary leads to better outcomes.

System builders and model developers are urged to prioritize reliability in multi-turn contexts, not just raw capability. This is especially true if you are building complex agentic systems where the impact of these issues is more prevalent.

LLMs are really weird. And all this weirdness is creeping up into the latest models too but it more subtle ways. Be careful out there, devs.

More insights and paper here: https://t.co/g3DpzS4MqW

[Richard Socher @RichardSocher]

Jevons Paradox and the AI revolution

Early industrial revolution: More efficient steam engines led to more coal use, not less.
Today's parallel: GPUs and intelligence are our "coal"

As intelligence gets cheaper:
• We won't just lose jobs that require intelligence
• We'll use intelligence in more places
• Tasks we believe need intelligence will skyrocket

Despite falling marginal costs, we'll see an explosion in intelligence use. More efficiency doesn't mean less consumption - it means more applications.

[freeCodeCamp.org @freeCodeCamp]

If you work with data, you'll probably need to know how to use SQL. It's a powerful tool for data extraction, manipulation, and analysis. In this guide, Joel teaches you the essential SQL concepts you'll need to know as a Data Analyst – with examples.
Search freeCodeCamp News or our app for: "Essential SQL Concepts for Data Analysts – Explained with Code Examples"

[Cesar Osorio @cesarosoriof]

PyData Global starts today (online) and you can ‘pay what you can’ to attend . Some of the interesting presentations here

[Cesar Osorio @cesarosoriof]

I just registered for PyData Global 2024 https://t.co/un186Kmj8N

[freeCodeCamp.org @freeCodeCamp]

Preparing for your job interviews can really help your chances when job hunting.

And this course covers 50 common interview questions for Deep Learning roles.

You'll learn about the basics plus neural networks, optimization, regularization, & more.

https://t.co/ILJRwqS7vG

[TechCrunch @TechCrunch]

Database startup Neo4j embraces AI to supercharge growth https://t.co/Uav6N1din1

[Neo4j @neo4j]

Finishing stunning presentations at #NODES2024 by @nsmith_piano @pacoid - but of course...there's so much more coming!
We have more to come! Stay tuned, and you can still join the event: https://t.co/9V92tv49fM

[Cesar Osorio @cesarosoriof]

@ykdojo Are you stopping by Lima ? I’d love to join you for lunch

[Toronto Machine Learning Society (TMLS) @TMLS_TO]

🚀 Ready for the AI event of the year?
Join us at the 8th Annual TMLS Summit in Toronto from July 10-15! Dive into hands-on workshops, strategic business sessions, and inspiring case studies. Connect with Canada's vibrant AI community!

📅 Tickets: https://t.co/8wQx3FpCMm

[François Chollet @fchollet]

One thing that even relatively senior ML people often fail to grasp is that deep learning models are curves fitted to a data distribution. You cannot expect them to solve tasks outside of their training distribution (which is the sort of thing that you need intelligence for).

"Emergent learning" is an incorrect label -- if a model demonstrates performance on task A that it wasn't trained on, that simply means that there is significant overlap between A and all the data that you did train on. Competence doesn't magically emerge out of nowhere.

[Garry Tan @garrytan]

Working on real projects, side projects, open source, and just making things for fun is the antidote to this

A lot of people with CS degrees can't actually build anything

But the world will unfold for you if you not only prove you can build, but that you build for fun

[Cesar Osorio @cesarosoriof]

“Embeddings are islands , we need to connect them via bridges” - Suhas Pai

[Cesar Osorio @cesarosoriof]

Interesting event today organized by ⁦@amirfzpr⁩ from AISC https://t.co/3QjTJTEXkG

[Cesar Osorio @cesarosoriof]

Interesting event today organized by ⁦@amirfzpr⁩ from AISC https://t.co/3QjTJTEXkG

[Cesar Osorio @cesarosoriof]

@DrDavidJoyner Wow , almost 20 years !

[PyData @PyData]

All PyData Global 2023 videos have been uploaded to our YouTube channel! Run over and catch any of the 100 talks you may have missed, or just want to experience all over again! 🌐

Link to our playlist: https://t.co/b8rtL2TK1i

[Richard Socher @RichardSocher]

My @TEDAI2023 talk is up. I share my thoughts on AI, its future and an anecdote of our 2018 paper inventing prompt engineering. It was famously rejected by anonymous reviewers :)

The best way to predict the future is to make it happen.

https://t.co/mEXru9Xlk7