AI Innovators, Gather Round

Learn about Nvidia’s AI that can modify voices and sounds, how Sparse Llama 3.1 is making GPU inference 5x faster, Apple’s challenges rolling out AI in China, and DreamRunner’s leap in open-source storytelling. Plus, don’t miss the top lifetime deals for lead generation and sales management. Let’s jump in. 🌟

In today’s knowledge-packed edition:

• Build, deploy and win! Join #BuildwithAI Hackathon 2024 

• Nvidia Shows AI Model That Can Modify Voices, Generate Sounds

• 5x Faster, 50% Smaller: New Open Source Sparse Llama 3.1 8B for Efficient GPU Inference

• Apple Hits Hurdles in China With AI Rollout

• DreamRunner: Next-Level Open Source LLM Storytelling

• Top 5 Lifetime Deals for Lead Generation and Sales Management

🤘 Build, Deploy and Win! Join #BuildwithAI Hackathon 2024 

Want to learn how to compete in a hackathon? Join us for #BuildwithAI Hackathon 2024 and compete for $25,000 in prizes!

 Why Join?

• Cash Prizes & Exclusive Awards: Over $25,000 up for grabs!

• Big Name Sponsors & Opportunities: Partner with industry giants like AMD and NVIDIA

• Earn Digital Badges: Showcase your skills on LinkedIn, recognized by leaders in AI

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Don’t miss this chance to boost your career, build impactful projects, and make a mark in AI! 

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 Hackathon Dates: December 6-9, 2024

🆕 Nvidia Shows AI Model That Can Modify Voices, Generate Sounds

Nvidia has unveiled Fugatto, an advanced AI model capable of modifying voices and generating novel sounds, aiming to enhance creativity in music, film, and video game production.

Fugatto can transform audio inputs, such as converting piano melodies into human vocals or altering speech accents and emotional tones. It also enables the creation of unique sound effects from textual descriptions, like making a trumpet sound like it's barking.

Despite its innovative features, Nvidia has expressed concerns about potential misuse and currently has no immediate plans to release Fugatto publicly. The company is still deliberating on how to safely release the technology.

⚡️ 5x Faster, 50% Smaller: New Open Source Sparse Llama 3.1 8B for Efficient GPU Inference

Neural Magic has introduced their latest innovation: Sparse Llama 3.1 8B, a new 50% pruned, GPU-compatible model that's changing the game in efficient AI deployment.

Key Highlights:

• Achieves 1.8x lower latency and 40% better throughput through sparsity alone

• Potential for 5x lower latency when combined with quantization

• Maintains 98.4% accuracy on Open LLM Leaderboard V1 for few-shot tasks

• Requires only 13B additional tokens for training, significantly reducing carbon footprint

Neural Magic's approach demonstrates that we can maintain high performance while dramatically reducing resource requirements.

Neural Magic's innovative combination of:

• SparseGPT technology

• SquareHead Knowledge Distillation

• Intelligent 50% parameter pruning

• Advanced quantization techniques

By significantly reducing the computational requirements while maintaining performance, Sparse Llama 3.1 8B represents a crucial step toward more environmentally conscious AI development.

👉️ Read more

🍎 Apple Hits Hurdles in China With AI Rollout

Apple is encountering challenges in launching its artificial intelligence (AI) models for iPhones and other products in China. The company must navigate China's complex regulatory environment, which favors collaborations with local partners for smoother approval processes.

Apple CEO Tim Cook's recent visit to China underscores the market's significance, contributing significantly to the company's revenue. Despite advancements in AI within the U.S., Apple's path in China is more difficult due to stringent regulations and competition from local tech giants like Huawei.

Apple has engaged in discussions with Chinese firms such as Baidu, ByteDance, and Moonshot to potentially utilize their AI technology. As a strategic response to these hurdles, Apple might opt for partnerships to facilitate the introduction of AI features in China, potentially delaying the AI rollout until the latter half of 2025 or later.

🌒 DreamRunner: Next-Level Open Source LLM Storytelling

Researchers from UNC Chapel Hill have introduced DreamRunner, a novel approach to AI video generation. 

DreamRunner introduces a dual-level planning system utilizing large language models (LLMs) to:

• Generate high-level scene sequences with character-driven events

• Create detailed, frame-specific motion and layout planning

• Ensure narrative coherence across multiple scenes

The second pillar of DreamRunner's architecture introduces a novel approach to motion learning. Through retrieval-augmented adaptation, the system analyzes and learns from real-world video examples, enabling it to recreate complex movements with unprecedented accuracy. 

In testing, the system demonstrated a 13.1% improvement in character consistency, an 8.56% enhancement in following textual instructions, and a remarkable 27.2% increase in transition smoothness compared to existing solutions.

👉️ Read More

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