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  • Make GPT go 10x Faster with PyTorch ⚡️

Make GPT go 10x Faster with PyTorch ⚡️

PLUS: ChatGPT's Training Data Vulnerability, and Meta's Decade Milestone

Today’s top AI Highlights:

  1. PyTorch’s new performance features to accelerate generative AI models

  2. ChatGPT Training Data Expose challenging its privacy and security mechanisms

  3. Meta announces models and datasets for audio generation, language translation, and dual-perspective AI understanding of human skills.

  4. Revolutionizing customer interaction with AI-powered website walkthroughs

& so much more!

Read time: 3 mins

Latest Developments 🌍

10x Faster GPT Models with PyTorch 🔥

How fast can transformer inference run with only pure, native PyTorch? PyTorch has released a series of performance features to accelerate generative AI models. They have created an LLM that is almost 10x faster than the baseline, using native PyTorch optimizations like torch.compile (a compiler for PyTorch models), GPU quantization, speculative decoding, and tensor parallelism.

Key Highlights:

  1. By using torch.compile, they reduced CPU overhead significantly. This optimization captured larger regions into a single compiled region, effectively reducing the time taken for the CPU to instruct the GPU.

  2. The implementation of techniques like speculative decoding and int4 quantization has led to notable speed improvements. Speculative decoding leverages a smaller model for initial predictions, enhancing the speed of the larger target model.

  3. The Llama-7B model achieved 241 tokens per second, while Llama-70B with tensor parallelism reached 80 tokens per second. These performance metrics are at or above current state-of-the-art levels.

Extracting Training Data from ChatGPT

A recent study by Google DeepMind, CMU, UC Berkeley researchers has uncovered a method to extract several megabytes of training data from ChatGPT, revealing potential security vulnerabilities in this widely used AI model. This finding challenges the perceived robustness of ChatGPT's training and alignment processes, raising important questions about privacy and security in AI models.

Key Highlights:

  1. Researchers developed an inexpensive technique to extract megabytes of ChatGPT’s training data, demonstrating potential to extract even larger quantities with increased querying costing about two hundred dollars.

  2. The study bypassed ChatGPT's alignment procedures, designed to prevent data regurgitation, revealing latent vulnerabilities in the model's ability to safeguard sensitive training data.

  3. The research differentiates between patching specific exploits and addressing the broader underlying vulnerabilities. While certain attack methods can be mitigated, broader issues related to data memorization and model divergence in language models like ChatGPT present ongoing challenges for developers and users alike.

Giving AI Dual Perspective ✍️

On completing a decade of FAIR, Meta has released announced new models, datasets, and updates spanning audio generation, translation, and multimodal perception. Audiobox enhances audio generation and editing, Seamless revolutionizes language translation, maintaining expression while improving streaming, while Ego-Exo4D provides AI models with a dual perspective to understand complex human skills.

Key Highlights:

  1. Audiobox is an audio generation model that utilizes voice inputs and text prompts to create diverse audio content, surpassing its predecessor Voicebox in performance and versatility.

  2. Seamless is a suite of AI language translation models that facilitate real-time, expressive cross-lingual communication, significantly enhancing the quality and authenticity of translations.

  3. Ego-Exo4D introduces a comprehensive dataset for research in video learning and multimodal perception, featuring first-person and third-person perspectives, to advance AI's understanding of complex human skills through diverse, real-world scenarios.

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Tools of the Trade ⚒️

  • Shape: AI-powered data analytics tool that interprets queries like an analyst, offering advanced SQL capabilities, automatic data visualizations, and integration with Slack for quick, accurate data insights.

  • ddle.dev: AI-powered tool that helps you to create interactive walkthroughs for your website. It's like a video call, but without the hassle of scheduling one. With ddle.dev you can record your website and share it with your customers.

  • Haven: fine-tune and run open-source LLMs quickly and efficiently, and build specialized LLMs for specific tasks without the need for coding or setting up complex infrastructure.

  • DryMerge: AI tool for creating event-driven workflows using your functions, tools, and APIs. It automates various tasks, supports multi-tenant data syncs, and offers a powerful, user-friendly setup with white-glove onboarding.

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Hot Takes 🔥

  1. The loom, horses, & all other tools don't have the 🧠 or agency to replace humans.AGI isn't a tool. It is a new species. It will have more 🧠 and agency than us. We will be "pets" while they are the "humans". We'll just hang out doing whatever while they work & take care of us. ~ Source

  2. We need a name for ChatGPT style prose, because I swear I can identify it in the wild. It has a certain vibe. Like it was written by a golden retriever. ~ Chris Albon

  3. Science, as a *PROFESSION*, really doesn't have any intrinsic checks and balances that would prevent it from spiraling out of control and becoming the exact antithesis of what it purportedly stands for. I've seen first hand this happen to fundamental Physics. ~ Bojan Tunguz

Meme of the Day 🤡

r/ProgrammerHumor - ItsTrue

That’s all for today!

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