Data Science at Home
Episodes
Wednesday May 03, 2023
Wednesday May 03, 2023
This is the first episode about the latest trend in artificial intelligence that's shaking up the industry - running large language models locally on your machine. This new approach allows you to bypass the limitations and constraints of cloud-based models controlled by big tech companies, and take control of your own AI journey.
We'll delve into the benefits of running models locally, such as increased speed, improved privacy and security, and greater customization and flexibility. We'll also discuss the technical requirements and considerations for running these models on your own hardware, and provide practical tips and advice to get you started.
Join us as we uncover the secrets to unleashing the full potential of large language models and taking your AI game to the next level!
Sponsors
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References
https://agi-sphere.com/llama-models/
https://crfm.stanford.edu/2023/03/13/alpaca.html
https://beebom.com/how-run-chatgpt-like-language-model-pc-offline/
https://sharegpt.com/
https://stability.ai/
Friday Oct 23, 2020
Neural search (Ep. 123)
Friday Oct 23, 2020
Friday Oct 23, 2020
Come join me in our Discord channel speaking about all things data science.
Follow me on Twitch during my live coding sessions usually in Rust and Python
This episode is supported by Monday.com
The Monday Apps Challenge is bringing developers around the world together to compete in order to build apps that can improve the way teams work together on monday.com.
Sunday Jul 26, 2020
GPT-3 cannot code (and never will) (Ep. 114)
Sunday Jul 26, 2020
Sunday Jul 26, 2020
The hype around GPT-3 is alarming and gives and provides us with the awful picture of people misunderstanding artificial intelligence. In response to some comments that claim GPT-3 will take developers' jobs, in this episode I express some personal opinions about the state of AI in generating source code (and in particular GPT-3).
If you have comments about this episode or just want to chat, come join us on the official Discord channel.
This episode is supported by Amethix Technologies.
Amethix works to create and maximize the impact of the world’s leading corporations, startups, and nonprofits, so they can create a better future for everyone they serve. They are a consulting firm focused on data science, machine learning, and artificial intelligence.
Friday Oct 18, 2019
Friday Oct 18, 2019
Join the discussion on our Discord server
In this episode, I am with Aaron Gokaslan, computer vision researcher, AI Resident at Facebook AI Research. Aaron is the author of OpenGPT-2, a parallel NLP model to the most discussed version that OpenAI decided not to release because too accurate to be published.
We discuss about image-to-image translation, the dangers of the GPT-2 model and the future of AI. Moreover, Aaron provides some very interesting links and demos that will blow your mind!
Enjoy the show!
References
Multimodal image to image translation (not all mentioned in the podcast but recommended by Aaron)
Pix2Pix:
https://phillipi.github.io/pix2pix/
CycleGAN:
https://junyanz.github.io/CycleGAN/
GANimorph
Paper: https://arxiv.org/abs/1808.04325
Code: https://github.com/brownvc/ganimorph
UNIT:https://arxiv.org/abs/1703.00848
MUNIT:https://github.com/NVlabs/MUNIT
DRIT: https://github.com/HsinYingLee/DRIT
GPT-2 and related
Try OpenAI's GPT-2: https://talktotransformer.com/
Blogpost: https://blog.usejournal.com/opengpt-2-we-replicated-gpt-2-because-you-can-too-45e34e6d36dc
The Original Transformer Paper: https://arxiv.org/abs/1706.03762
Grover: The FakeNews generator and detector: https://rowanzellers.com/grover/
Monday Sep 23, 2019
Monday Sep 23, 2019
Join the discussion on our Discord server
In this episode, I am with Aaron Gokaslan, computer vision researcher, AI Resident at Facebook AI Research. Aaron is the author of OpenGPT-2, a parallel NLP model to the most discussed version that OpenAI decided not to release because too accurate to be published.
We discuss about image-to-image translation, the dangers of the GPT-2 model and the future of AI. Moreover, Aaron provides some very interesting links and demos that will blow your mind!
Enjoy the show!
References
Multimodal image to image translation (not all mentioned in the podcast but recommended by Aaron)
Pix2Pix:
https://phillipi.github.io/pix2pix/
CycleGAN:
https://junyanz.github.io/CycleGAN/
GANimorph
Paper: https://arxiv.org/abs/1808.04325
Code: https://github.com/brownvc/ganimorph
UNIT:https://arxiv.org/abs/1703.00848
MUNIT:https://github.com/NVlabs/MUNIT
DRIT: https://github.com/HsinYingLee/DRIT
GPT-2 and related
Try OpenAI's GPT-2: https://talktotransformer.com/
Blogpost: https://blog.usejournal.com/opengpt-2-we-replicated-gpt-2-because-you-can-too-45e34e6d36dc
The Original Transformer Paper: https://arxiv.org/abs/1706.03762
Grover: The FakeNews generator and detector: https://rowanzellers.com/grover/