Відео

I'm not even a particularly advanced player and I guarantee I would destroy that robot. It looks to be barely beyond advanced amateur in my opinion. Any club player would outscore the robot 2 to 1 or more. Most club players smash anything that goes over the net by more than about 6 inches (and often a lot less than that). To advance very much it's speed needs to increase by a factor of 2 or 3.

Here’s a link to the code I ran in the video. github.com/buaacyw/MeshAnythingV2 And here’s a link to the Rodin website where I created the 3D character. hyperhuman.deemos.com/rodin

"he" this, "him" that. Is that thumbnail narrator AI-generated?

Could not deal with the massive spin of advanced players.

Here’s a link to the full paper: Achieving Human Level Competitive Robot Table Tennis arxiv.org/pdf/2408.03906

Here’s a link to the SharkEye website. sharkeye.org/#our-process And here’s a link to the documentation page for YOLO. docs.ultralytics.com/

they should use this to end world hunger and do cancer research pleaseeeeeeeeeeeeeeeeeeeeeeee

Here’s a link to the full article from Google DeepMind. AI achieves silver-medal standard solving International Mathematical Olympiad problems deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level/

Here’s a link to the blog post I quoted from in the video. Open Source AI Is the Path Forward about.fb.com/news/2024/07/open-source-ai-is-the-path-forward/

If you’re interested in digger deeper into this topic, I highly recommend this excellent article by Ed Bott on ZDnet, which includes some very helpful historical context. “What caused the great CrowdStrike-Windows meltdown of 2024? History has the answer.” www.zdnet.com/article/what-caused-the-great-crowdstrike-windows-meltdown-of-2024-history-has-the-answer/

Great video! Thank you for the clear explanation. The calm tone made it easier to undertand.

Here’s a link to the paper I featured in this video: “Mixture of A Million Experts,” by Xu He at Google DeepMind arxiv.org/pdf/2407.04153

At the very end of this video there’s a snippet from a brilliant performance of the song “Daisy Bell: A Bicycle Built For Two,” by permission from Julien Neel. (Thank you Julien!) Here’s his website: julienneel.sellfy.store/ All four singers in the barbershop quartet are Julien. It’s brilliant - and amazing. Here’s a link to the full song on UA-cam. ua-cam.com/video/JmiNlZAiDqo/v-deo.html

Here’s a link to the paper this video is about: “Discovering Preference Optimization Algorithms with and for Large Language Models” arxiv.org/pdf/2406.08414

Please check your microphone volume before upload, you are DRAMATICALLY quieter than any of the sound effects or your end card. I'd hazard a guess at around 12dB quieter.

You could probably get it running at home through a smart scalar API like Ollama with 4 A6000s, 512gb of system RAM, and a pair of Intel Scalable CPUs with AVX-512 cores, it'll be around $10k to build on used parts. It won't be snappy, 2 minutes per response at least, but it's cheaper than renting a whole DGX for a month. A 22.3k entry synthetic dataset generated by continually inferring desireable results with Nemotron over a month should be good enough to start training a smaller model to a far higher standard than it's natural dataset counterpart could provide, and look at that, you'll also have hardware good enough for training 32B models already on-hand by the end.

That's mixtral though isn't it just getting memory throttled

No performance gains on CPU unless you use their models *and* you have avx2 instruct set, so meh. I'll stick to my current project of making ultra slim, CPU only mini models that challenge mainstream, thanks.

Very interesting. Is there a way to link powerinfer2 to sillytavern ?

don't make such loud noises in the video

phone farms might take this on 🍿

Here’s a link to the paper I cited in the video. PowerInfer-2: Fast Large Language Model Inference on a Smartphone arxiv.org/abs/2406.06282

Agent smith.

As promised in the video, here’s a link to the technical report we looked at. Nemotron-4 340B Technical Report d1qx31qr3h6wln.cloudfront.net/publications/Nemotron_4_340B_8T_0.pdf

I like this test! However I think the first math question was very “textbook” in nature such that if it understood the key words could probably directly copy from source text. Similar to canterberry tales. But the middle question required specialized knowledge and further subtle understanding. Nice to know gtp4.0 isn’t perfect at least! At leas lt not yet…

Here’s a link to the full list of models accessible via Ollama. There are 92 models currently listed there. www.ollama.com/library And here’s the download page I showed in the video. www.ollama.com/

My man Beautifully said

As promised in the video, here’s a link to the announcement about the new AI Master Group podcast, which launches on July 7. aimast.org/jim-griffin/

Here’s a link to the paper I cited by Bowen Xu, “What is Meant by AGI? On the Definition of Artificial General Intelligence” arxiv.org/html/2404.10731v1

Here’s a link to the announcement page, which has quite a few additional videos and images beyond what I showed. Hello GPT-4o : openai.com/index/hello-gpt-4o/

Hope you are having a wonderful weekend, Jim.

Thank you to Lemon for permission to use parts of the track, Mr. Bongo! Here's a link to Lemon / Freshly Squeezed on Sound Cloud soundcloud.com/freshlysqueezed and here's a link to Ursula1000 soundcloud.com/ursula1000

As promised in the video, here's a link to the original paper with technical details about BASE TTS. assets.amazon.science/6e/82/1d037a4243c9a6cf4169895482d5/base-tts-lessons-from-building-a-billion-parameter-text-to-speech-model-on-100k-hours-of-data.pdf Best wishes!

Nice summary. But the engine used for Mona Lisa /Audrey Hepburn seems fundamentally different from the "AI announcers" because it obviously requires an input video of someone talking, which it applies to the photo - rather than generating new facial movement solely from text like the others. So the Mona Lisa one seems to have more in common with a deep fake.

Let me know if you want to connect to Ramsu or any of the founders at solus.ai They’re great people that I know well.

Audrey H dubbed Natalie Portman all in

As promised in the video, here’s a link to the page where you can find more information about EMO, including more amazing videos created by that tool. Check out “AI Girl generated by ChilloutMix,” and also Leonardo Wilhelm DiCaprio rapping Godzilla. EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions humanaigc.github.io/emote-portrait-alive/

Here’s a link to the thread I mentioned in the video from the OpenAI Developer Community page, where more than a dozen developers posted more than 60 different messages over a six month period of time, regarding pricing a Gen AI solution. There’s much more detail there than I could cover in a short video, so it’s worth a look. How to accurately price a gpt-4 chatbot? community.openai.com/t/how-to-accurately-price-a-gpt-4-chatbot/347250

As promised in the video, here’s a link to the tutorial by Patrick at AssemblyAI showing how to get started with Gradio. At about 8 minutes in, he shows an LLM being pulled into Gradio from Hugging Face. ua-cam.com/video/eE7CamOE-PA/v-deo.html And here’s a link to the blog I mentioned, written by Vellum founder Akash Sharma, showing the mechanics of testing competing LLMs against some of the metrics I mentioned in the video. www.activeloop.ai/resources/how-to-compare-large-language-models-gpt-4-3-5-vs-anthropic-claude-vs-cohere/

As promised in the video, here’s a link to the CNBC page with the story about Jeff McMillan’s promotion last week, including an embedded video, which is a previously-recorded interview between McMillan and CNBC’s Hugh Son about the recent generative AI project at Morgan Stanley. Morgan Stanley names a head of artificial intelligence as Wall Street leans into AI www.cnbc.com/2024/03/14/morgan-stanley-names-head-of-artificial-intelligence-jeff-mcmillan.html

As promised in the video, here’s a link to the video walk of FAISS through by James Briggs. James Briggs, Faiss - Introduction to Similarity Search ua-cam.com/video/sKyvsdEv6rk/v-deo.html And here’s a link to the page I showed, comparing 15 different vector databases. The link name says 2023, but it was updated again in 2024. Best 15 Vector Databases for 2024 [Top Picks] lakefs.io/blog/12-vector-databases-2023/

❤❤❤❤❤

People without souls 🫠😖😖😖👎👎👎

As promised, here’s a link to the Sora announcement page OpenAI: Creating video from text openai.com/sora And here’s a link to the technical report. Video generation models as world simulators openai.com/research/video-generation-models-as-world-simulators

Thx heaven for sphere packing

My uneducated opinion( you didn’t ask). Spin networking is your best bet to really understanding a space age. The rest is an early age of development wow

There are millions of problems to solve every micro second. Some math choices are more correct. Math is math

Does AI know how to encourage human desires to study. It seems to be addicting Without offering itself as a bonafide educator

"Redacted" on UA-cam looked at one AI company which produces 'historical images' and produced a Chinese female Nazi and a black male Nazi when asked to produce a profile of a Nazi. When asked to produce a picture of Elon Musk, Elon had turned black..! On Al-Jazeera, a couple days ago (it's the 2nd of March, 2024 today), AI was implicated in the Israeli bombings of civilians, women and children, in Palestine...

As I understood it there are no "reasoning abilities" which emerge. Its a feature to sound like coherent sentences made by reasoning but its a heuristic output based on its large trainingbase and some other factors. So in any cases it had enough trainingdata where similar events took place and it reacted to that pattern it doesn't mean that it can reason the same way in altered or more compicated scenarios. The "2 Jug " riddle example shows quickly how this apporach creates more unintended limitations sometimes.