Lifeboat Foundation

Some models are available to users without Chinese phone numbers, while open-source platforms provide other workarounds.

A Mormon Transhumanist has trained a chatbot that was trained on his entire collection of writings, internet social media posts, and presentations.

I’ve merged with artificial intelligence. Well, I’m working on it. And I’m excited to share the results with you.

! Trained on everything that I’ve written publicly since 2000, he might be better at Mormon Transhumanism than I am.

Continue reading “Meet LincGPT” »

An extremely cool application of large language models in combination with other AI tools such as models for text-to-speech and speech-to-text, image recognition and captioning, etc.

We created a robot tour guide using Spot integrated with Chat GPT and other AI models to explore the robotics applications of foundational models.

Joscha Bach meets with Ben Goertzel to discuss cognitive architectures, AGI, and conscious computers in another theolocution on TOE.

- Patreon: / curtjaimungal (early access to ad-free audio episodes!)
- Crypto: https://tinyurl.com/cryptoTOE
- PayPal: https://tinyurl.com/paypalTOE
- Twitter: / toewithcurt.
- Discord Invite: / discord.
- iTunes: https://podcasts.apple.com/ca/podcast…
- Pandora: https://pdora.co/33b9lfP
- Spotify: https://open.spotify.com/show/4gL14b9…
- Subreddit r/TheoriesOfEverything: / theoriesofeverything.
- TOE Merch: https://tinyurl.com/TOEmerch.

Continue reading “Joscha Bach Λ Ben Goertzel: Conscious AI, LLMs, AGI” »

Are you ready for artificial intelligence?

Curt’s “String Theory Iceberg”: https://youtu.be/X4PdPnQuwjYMain episode with Bach and Goertzel (October 2023): https://youtu.be/xw7omaQ8SgA?list=PLZ7ikzmc6zlN6E8KrxcYCWQIHg2tfkqvR Consider signing up for TOEmail at https://www.curtjaimungal.org

One of the significant challenges in AI research is the computational inefficiency in processing visual tokens in Vision Transformer (ViT) and Video Vision Transformer (ViViT) models. These models process all tokens with equal emphasis, overlooking the inherent redundancy in visual data, which results in high computational costs. Addressing this challenge is crucial for the deployment of AI models in real-world applications where computational resources are limited and real-time processing is essential.

Current methods like ViTs and Mixture of Experts (MoEs) models have been effective in processing large-scale visual data but come with significant limitations. ViTs treat all tokens equally, leading to unnecessary computations. MoEs improve scalability by conditionally activating parts of the network, thus maintaining inference-time costs. However, they introduce a larger parameter footprint and do not reduce computational costs without skipping tokens entirely. Additionally, these models often use experts with uniform computational capacities, limiting their ability to dynamically allocate resources based on token importance.

🚀 [FREE AI WEBINAR] ‘Learn how to fine-tune SAM 2 with your own data.’ (August 8, 2024 10 am PST) [Promoted].

In the next 20 years, AI will eat software.

“We made it possible for the computer to write software by itself.”

—NVIDIA CEO Jensen Huang on the future of AI

Here they come… 🦾🤖

And this shows one of the many ways in which the Economic Singularity is rushing at us. The 🦾🤖 Bots are coming soon to a job near you.

NVIDIA unveiled a suite of services, models, and computing platforms designed to accelerate the development of humanoid robots globally. Key highlights include:

Continue reading “NVIDIA Accelerating the Future of AI & Humanoid Robots” »