First-ever Opensource AI wearable device

Today’s top AI Highlights:

1. Tesla enables full self-driving for all the customers

2. Adobe releases the GenAI studio to supercharge the content pipeline

3. Opensource AI wearable device with DIY feature

4. Use opensource LLMs locally on Apple devices without internet

& so much more!

Read time: 3 mins

1. https://stability.ai/news/introducing-stable-code-instruct-3b

Elon Musk has made it mandatory for every new Tesla buyer in North America to experience the company’s Full Self-Driving (FSD) system firsthand before they drive off with their vehicle. This initiative requires employees to install and demonstrate the latest FSD version 12.3.1 to familiarize customers with its capabilities through a short test ride. To get more users onboard, Musk has further announced a one-month free trial of FSD for all U.S. Teslas capable of the system.

Currently, Tesla offers two subscription tiers on the basis of the hardware and software configurations in the car:

• Basic Autopilot to FSD: If your Tesla vehicle currently has the Basic Autopilot package, upgrading to the FSD capability will cost $199.00 per month. The Basic Autopilot package includes features like Traffic-Aware Cruise Control and Autosteer, which assist in maintaining a safe speed and steering within clearly marked lanes.

• Enhanced Autopilot to FSD: For vehicles equipped with Enhanced Autopilot, the upgrade to FSD capability is priced at $99.00 per month. Enhanced Autopilot adds functionalities such as Navigate on Autopilot, Auto Lane Change, Autopark, Summon, and Smart Summon to the basic features.

Musk claims that “Almost no one actually realizes how well (supervised) FSD actually works.” While many FSD features are still in Beta and the features are still improving, the more customers test FSD, the better Tesla will be able to make it.

At its Annual Summit, Adobe has released a suite of generative AI tools in its Gen Studio that optimizes the entire content supply chain of enterprises. The studio now provides an end-to-end solution for content marketeers right from the stage of planning workflows, creating content, asset management, delivery to reporting and getting insights from the campaigns.

Key Highlights:

Workflow and Planning:

• Adobe Workfront Planning provides a comprehensive view of all marketing activities, connecting assets, timelines, project status, and performance metrics for efficient management.

• Studio integration with Workfront and Frame.io streamlines content review and approvals, ensuring seamless collaboration. When a project is initiated in Workfront, a corresponding project is automatically created in Frame.io for content sharing and feedback tracking.

Asset Creation and Production:

• Adobe introduces Firefly Services, offering 20 generative and creative APIs for content generation and editing, including resizing, object/background replacement, and content assembly into final assets.

• Enterprises can customize Firefly models to generate brand-specific content, enhancing content relevance to products and brand identity.

Asset Management:

• The Assets content hub enables efficient distribution of brand-governed assets (images, icons, illustrations, PDFs, videos, etc.) across organizations, partners, and agencies via a unified platform, facilitating collaboration and sharing.

Delivery and Activation:

• Sites variant generation allows for marketing content customization for different audience segments (e.g., teenagers, parents, retirees), enhancing message resonance with specific group preferences.

• Adobe Journey Optimizer enables automatic creation of customized emails with images and text, ideal for targeted offers, especially during the holiday season.

Reporting and Insights:

• Adobe Content Analytics provides in-depth analysis of AI-generated content performance, identifying appealing elements (e.g., colors, styles) to the audience, aiding in content optimization strategies.

Nik Shevchenko’s project, Whomane’s Friendoffers an affordable alternative to high-priced AI wearables like Humane’s AI Pin and Ray Ban Smart Glasses. He has made the design of his AI wearable open-source, showcasing that creating AI-powered wearables can be simple and cost-effective. This marks the first-ever open-source AI wearable, highlighting an innovative and accessible approach to wearable technology.

• Open Source Design: Nik Shevchenko’s AI wearable, Whomane’s Friend, features an open-source design, making it accessible for anyone to build and modify.

• Cost-Effective: Costs less than $100 to assemble, significantly lower than many competitors in the market.

• Easy Assembly: Composed of just four main components readily available on Amazon, making it straightforward to assemble even for beginners.

• Personalization and Utility: Offers real-time AI audio processing and the capacity for users to add custom software. A camera can also be added for enhanced functionalities.

• Versatile Use: Suitable for a wide range of applications including recording, receiving proactive feedback, and software development experimentation.

1. Tracecat: Open source automation platform for security teams. Particularly useful for small to mid-sized teams, it equips them with AI-assisted workflow creation and case management tools, including a drag-and-drop builder, advanced categorization, deduplication, AI-assisted labeling, an analytics dashboard, and more.

2. Zerve AI: A unified development space for exploration, collaboration, building, and deployment of AI projects with innovative features like language interoperability and parallel processing. It combines the functionalities of notebooks and IDEs, enabling data science and ML teams to work in a stable, integrated coding environment with automated cloud infrastructure.​

3. Private LLM: Use AI chatbot on Apple devices without internet, keeping your information completely on-device, safe and private. It supports a variety of open-source LLM models, including Google Gemma, Microsoft Phi-2, and the Mistral and Llama 2 families, on both your iPhones, iPads and Macs.

4. Dawn: Analytics for AI products by transforming user inputs and model outputs into meaningful metrics, facilitating understanding through user segmentation, churn analysis, search request categorization, content moderation, and response flagging.

😍 Enjoying so far, share it with your friends!

1. Spoke to a Microsoft engineer on the GPT-6 training cluster project. He kvetched about the pain they’re having provisioning infiniband-class links between GPUs in different regions.
   Me: “why not just colocate the cluster in one region?” Him: “Oh yeah we tried that first. We can’t put more than 100K H100s in a single state without bringing down the power grid.”🤯 ~

   Kyle Corbitt

2. Cheat sheet for world domination in 2024
   > insanely hype up AI
   > claim super intelligence / AGI is around the corner
   > create hype, mystery, and intrigue
   > claim it can be very dangerous
   > insist it should be regulated
   > ensure that the regulation kills open-source
   > restrict foundational AI model development to a handful of labs
   > raise boatloads of money to establish AI dominance
   Total World Domination Achieved!! ~
   Bindu Reddy

That’s all for today! See you tomorrow with more such AI-filled content.

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