Adam Spotton ☕

Founder Webshrinker, VocalVector, #Homebrewer 🍺│ │#MachineLearning #ArtificialIntelligence #BigData #Linux #AWS #SoftwareEngineer

[Adam Spotton ☕ @AdamSpotton]

@johnrushx The website is https://t.co/Ff7TgW92Se if you're interested

[Adam Spotton ☕ @AdamSpotton]

@johnrushx I am the founder of VocalVector which you can use on the phone or video meetings, we have agents for receptionist and full sales/BDR. They natively speak English/Spanish too

[Adam Spotton ☕ @AdamSpotton]

@pmarca Interesting times, thanks for sharing!

[Adam Spotton ☕ @AdamSpotton]

@rohanpaul_ai Interesting

[Adam Spotton ☕ @AdamSpotton]

Completely agree, conversational AI is reshaping how we interact with tools and perform knowledge work.

@VocalVector has been exploring this through AI agents that handle real-time interactions, even inbound calls. Here's a demo of our sales agent in action: https://t.co/qTNXP9NURY

[Adam Spotton ☕ @AdamSpotton]

@rileybrown_ai @DonAllenIII Great demo!

[Adam Spotton ☕ @AdamSpotton]

AGI has also been overhyped. It's interesting but also not needed for the vast majority of applications where current generative AI can be used.

A good example of this is how it's being used at https://t.co/eAa4jsV6zd

[François Chollet @fchollet]

Many people have been recognizing that AGI won't be coming from mere scaling of current tech, and that generative AI has been severely overhyped. This is all true. But those people often conclude, "therefore AI is not going to be transformative -- this is a nothingburger". Absolutely not.

AI (both current and near-future tech) *will* transform nearly every industry, and we're still only in the very first steps of that process. Generative AI may be a bubble, but AI is going to be bigger in the long run than what almost all observers currently anticipate.

[Adam Spotton ☕ @AdamSpotton]

@mitchell_sorkin Check out https://t.co/eAa4jsUyJF this is what we do. Full AI sales and support agents on the phone and video calls!

[Adam Spotton ☕ @AdamSpotton]

Open AI models +1️⃣

[Andrej Karpathy @karpathy]

LLM model size competition is intensifying… backwards!

My bet is that we'll see models that "think" very well and reliably that are very very small. There is most likely a setting even of GPT-2 parameters for which most people will consider GPT-2 "smart". The reason current models are so large is because we're still being very wasteful during training - we're asking them to memorize the internet and, remarkably, they do and can e.g. recite SHA hashes of common numbers, or recall really esoteric facts. (Actually LLMs are really good at memorization, qualitatively a lot better than humans, sometimes needing just a single update to remember a lot of detail for a long time). But imagine if you were going to be tested, closed book, on reciting arbitrary passages of the internet given the first few words. This is the standard (pre)training objective for models today. The reason doing better is hard is because demonstrations of thinking are "entangled" with knowledge, in the training data.

Therefore, the models have to first get larger before they can get smaller, because we need their (automated) help to refactor and mold the training data into ideal, synthetic formats.

It's a staircase of improvement - of one model helping to generate the training data for next, until we're left with "perfect training set". When you train GPT-2 on it, it will be a really strong / smart model by today's standards. Maybe the MMLU will be a bit lower because it won't remember all of its chemistry perfectly. Maybe it needs to look something up once in a while to make sure.

[Adam Spotton ☕ @AdamSpotton]

@tibo_maker We've used the @VocalVector platform for conversational travel agents and also as a real time co-host for YouTube streams

[Adam Spotton ☕ @AdamSpotton]

@tdinh_me This happened to me and took a while to track down. Turns out it was when Docker containers were starting or terminating and having IPv6 enabled on the host. Disabling IPv6 fixed it.

[Adam Spotton ☕ @AdamSpotton]

@girdley Congratulations, it just passed the 200k mark!

[Adam Spotton ☕ @AdamSpotton]

https://t.co/SXzmyGnln7

[Adam Spotton ☕ @AdamSpotton]

For anyone interested in using an #AI personal fitness trainer in the new year, give the #GPT that I made on OpenAI a try. It's free and available to everyone.

It'll work with you to craft the right workout routine for your goals.

Link in the comments!

[Adam Spotton ☕ @AdamSpotton]

@svpino Always have a go-to side project that is fun to work on. You never know where it will go but if you don't enjoy working on it, it won't go far.

[Adam Spotton ☕ @AdamSpotton]

@CommonCrawl Congratulations CCF, keep up the great work!

[Adam Spotton ☕ @AdamSpotton]

@CommonCrawl That's great, thank you for checking into and fixing the RSS feed!

[Adam Spotton ☕ @AdamSpotton]

The project can be found on GitHub:

https://t.co/fDzM2vpEWb

[Adam Spotton ☕ @AdamSpotton]

Had a chance to test the latest Fooocus image generation model. It's free, quick, not that resource intensive, and can run on Colab which is great.

It seems to still have issues with rendering faces, fingers, and artifacts around eyes though.

Worth keeping an eye on its progress!

#stablediffusion #midjourney