Why LLMs are not as powerful to replace a developer just yet.

YouTube

Why is everyone LYING?

***🚀*** https://neetcode.io/ - A better way to prepare for Coding Interviews ***🧑‍💼*** LinkedIn: https://www.linkedin.com/in/navdeep-singh-3aaa14161/ ***🐦*** Twitter: https://twitter.com/neetcode1 ***⭐*** BLIND-75 PLAYLIST: https://www.youtube.com/watch?v=KLlXCFG5TnA&list=PLot…

OpenAI Co-founder Andrej Karpathy explains the new computing AI paradigm

Just a kind reminder that @GPT_DialogBot is working, while the ChatGPT website is down.

O - Omnimodel - 2x Faster GPT4, slightly more intelligence - Reasons across text, voice and vision with ONE model - GPTs will be available for FREE users with GPT-4o - API (pricing 50% cheaper)

O - Omnimodel

- 2x Faster GPT4, slightly more intelligence
- Reasons across text, voice and vision with ONE model

- GPTs will be available for FREE users with GPT-4o
- API (pricing 50% cheaper)

source

Elon musk sued Sam Altman

Openai

OpenAI and Elon Musk

We are dedicated to the OpenAI mission and have pursued it every step of the way.

It's clever, probably really smarter than GPT-4.
Confirmed with AI Explained channel.

Well, still, not nearly an AGI yet :)

YouTube

The New, Smartest AI: Claude 3 – Tested vs Gemini 1.5 + GPT-4

Claude 3 is out and Anthropic claim it is the most intelligent language model on the planet. The paper was released 90 minutes ago, and I’ve read it in full and the release notes. I’ve tested the model and compared it to Gemini 1.5 and GPT-4 in image analysis…

*? Deep Learning is a Strange Beast*

Hey there! Just finished watching an AI podcast, where they discussed the book "Understanding Deep Learning", which is a nice start for a newbie in understanding the Deep Learning.

? The discussion is thought provoking and criticizes some of our general understanding of how ChatGPT work, and the "neuron" analogy, which is often made when describing the AI.

Thought you might find it fascinating. It's more about the ideas behind deep learning than just coding.

Here's a quick rundown:
*?Overview*
• The book itself delves into neural networks, various models, generative models, reinforcement learning, and the uniqueness of deep neural networks.

*?*Key Concepts
• It covers everything from neural network architectures to different models like convolutional networks and transformers.
• There's a special focus on generative models like GANs and Diffusion Models, and even a bit on reinforcement learning.

*? *Deep Learning Insights
• It discusses why deep neural networks work, looking into their architecture and generalization.
• Also, it delves into overparameterization and why these huge models can be trained successfully. Quite intriguing!

*? *Ethical Considerations
• The book doesn't shy away from the ethical side of AI, discussing the impact on society, like how the jobs are replaced by those who able to perform faster and better with AI tools.

*?‍? Author's Journey*
• Simon, the author, shares his journey through psychology, neuroscience, augmented reality, and deep learning. His insights are pretty cool and add a personal touch.

*? Interesting Numbers*
• The book is loaded with 275 figures and Python notebooks. Plus, it talks about big models like AlexNet and GPT-3, which have millions and billions of parameters.

YouTube

Deep Learning is a strange beast.

In this comprehensive exploration of the field of deep learning with Professor Simon Prince who has just authored an entire text book on Deep Learning, we investigate the technical underpinnings that contribute to the field's unexpected success and confront…