GPT-4 Fails the Turning Test 🙅‍♀️

PLUS: Phind Model Surpasses GPT-4 in Coding, Pre-Book Nvidia GPUs with Amazon, Fine-tune Image Generation Models

Today’s top AI Highlights:

1. Phind Model Beats GPT-4 at Coding

2. GPT-4 Put through the Turing Test

3. Pre-book Nvidia H100 GPUs in Advance with Amazon

4. Stability AI’s New Image Capabilities and APIs

5. Google’s New Features for Enhanced Appearance and Shopping

& so much more!

Read time: 3 mins

Latest Developments 🌍

Surpassing GPT-4 in Coding at 5x Speed 🚀

Phind’s 7th-generation model sets new standards in coding by surpassing GPT-4 in both efficiency and performance. With a remarkable 5x increase in processing speed, the model, built on the CodeLlama-34B fine-tunes, has achieved an unprecedented 74.7% pass@1 on HumanEval.

The model can process up to 16k tokens and supports inputs of up to 12k tokens on the website. Leveraging TensorRT-LLM library from NVIDIA, the Phind team has successfully achieved the acceleration enabling users to obtain high-quality coding solutions within a mere 10 seconds.

GPT-4 Put Through the Turing Test 📝

While Turing Test has been put to considerable criticism, it still continues to be relevant as an assessment of naturalistic communication and deception. Researchers at UC San Diego put GPT-4 to this ultimate test of human-like intelligence in which GPT-4 outperformed ELIZA and GPT-3.5, but it fell short of human participants, revealing intriguing insights.

Key Highlights:

• GPT-4 excelled by passing the Turing Test in 41% of games, showcasing its linguistic prowess. However, it was unable to match human participants who achieved a 63% success rate, underlining the multifaceted nature of the test beyond intelligence alone.

• The study underscores the critical ability of AI to deceive human interrogators into believing it's human. This has severe implications from automation in client-facing roles to the spread of misinformation.

• Despite GPT-4's substantial performance, the study suggests that none of the AI witnesses tested met the 50% success or human parity criteria, indicating that GPT-4 did not fully pass the Turing Test as per the study's findings.

Planning Ahead for ML Success 🔖

To addresses the growing demand for GPU capacity in the face of limited industry-wide supply, Amazon introduces Amazon EC2 Capacity Blocks for ML, providing a solution for customers with fluctuating capacity needs during various phases of R&D. It will let you reserve GPU instances for future use, with a focus on EC2 P5 instances powered by NVIDIA H100 Tensor Core GPUs.

This solution operates akin to hotel room reservations, allowing you to pre-book the desired capacity, duration, and instance size from a range of options. It the available in cluster sizes of one to 64 instances with 8 GPUs per instance, and can be booked up to 8 weeks in advance.

Now you can effortlessly plan your ML development trajectory, be it for training, fine-tuning, or running experiments.

Stability AI’s New Image Capabilities and APIs 💫

Stability AI has introduced new text-to-image offerings for design professionals including advanced APIs for businesses, doubling-down on their heritage product - beautiful images - better, cheaper, and faster (and now in 3D!)

Key Highlights:

• Sky Replacer, designed with real estate professionals in mind, lets you effortlessly swap out the sky in photos with nine alternatives, enhancing the visual appeal of properties for increased buyer attraction.

• Stable 3D simplifies 3D content creation for designers and developers, enabling automatic generation of draft-quality textured 3D objects from image or text prompts.

• Empowering enterprises and developers, Stable FineTuning provides a turnkey integration solution for rapid customization of images, objects, and styles, catering to industries such as entertainment, gaming, advertising, and marketing.

Google Empowers Small Business with Generative AI 🏭

Google has announced new updates to its Shopping platform, aiming to empower small businesses with generative AI and enhance your shopping experience. The updates will be rolled out this month.

Key Highlights:

• Google is launching Product Studio, an AI-powered tool that enables merchants to make visual adjustments to product images, remove backgrounds, and personalize product listings for seasonal campaigns with just text prompts.

• Merchants in the US can now label themselves with the "small business" attribute, allowing shoppers to easily distinguish mom-and-pop-style stores. These businesses and their products will be clearly labelled in Maps and Search.

• The knowledge panel in Google Search is expanded to display comprehensive information about retailers, including reviews, shipping and returns policies, and customer service details.

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Tools of the Trade ⚒️

• CoPilot.Live: Create your own CoPilot that can integrate with your website or SaaS product and can help you perform tasks on your product/website by just taking text prompts, boosting overall productivity.

• Saner.AI: AI knowledge management assistant that helps streamline and centralize information, enabling instant note capture, smart organization, and AI-driven content generation.

• Jumble: AI-powered, distraction-free journaling app that helps users gain clarity, discover personal insights, and achieve growth through habit formation and retrospective tools.

• Empy AI: Monitors team communication, and detects and resolve team conflicts in real-time, along with data-driven insights to improve team emotional well-being and reduce employee churn rates.

• Aporia: An ML observability platform that provides comprehensive insights into model performance and health, along with live alerts for drift and bias, and in-depth investigation capabilities, all without data leaving your stack.

😍 Enjoying so far, TWEET NOW to share with your friends!

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Hot Takes 🔥

• Laws to ensure AI applications are safe, fair, and transparent are needed. But the White House's use of the Defense Production Act—typically reserved for war or national emergencies—distorts AI through the lens of security, for example with phrases like "companies developing any foundation model that poses a serious risk to national security." ~ Andrew Ng

• You only need <100M parameters to build a literal killer AI from hell. Download a Mask R-CNN object detector. Train an ethnicity classifier. Mount a gun on Spot robot dog.
  Pure evil with a fraction of LLMs’ FLOPs. ~ Jim Fan

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Meme of the Day 🤡

Source

That’s all for today!

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