AI Innovators, Gather Round

Alibaba’s Qwen team is pushing the boundaries of AI with advanced reward models that tackle complex mathematical challenges. Meanwhile, Apple has joined a consortium to pioneer next-gen AI data center technology, setting the stage for more efficient AI infrastructure. In the realm of compact AI, a new 8B LLM outshines GPT-4V in visual tasks and runs efficiently on mobile devices. Stay ahead with the latest updates!🧠

In today’s knowledge-packed edition:

• Do You Want to Enter New Markets? You can! By building strong AI Alliances…

• Synthesia Snaps up $180M at a $2.1B Valuation For Its B2B AI Video Platform

• Alibaba's Qwen Team Handle Complex Mathematical Operations With New Process Reward Models

• Apple Joins Consortium to Help Develop Next-Gen AI Data Center Tech

• New 8B LLM Outperforms GPT-4V in Visual Tasks While Running on Your Phone

• 5 Best AI Tools for Ads Creation

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💰️ Synthesia Snaps up $180M at a $2.1B Valuation For Its B2B AI Video Platform

Synthesia, a London-based AI startup specializing in creating realistic video avatars for corporate communications, has secured $180 million in a Series D funding round, elevating its valuation to $2.1 billion.

The round was led by New Enterprise Associates, with participation from existing investors such as Google Ventures and Accel Partners. Founded in 2017, Synthesia plans to utilize the new capital to enhance the lifelike quality of its avatars and expand its AI-powered video platform across markets including Japan, Australia, Europe, and North America.

The company boasts a client base that includes major corporations like Zoom, Xerox, and Microsoft, and has been recognized as one of the UK’s most promising AI startups.

Despite facing competition from U.S. and Chinese tech giants, CEO Victor Riparbelli expressed confidence in the UK’s potential to become a leading AI superpower, bolstered by recent supportive government policies.

➗ Alibaba's Qwen Team Handle Complex Mathematical Operations With New Process Reward Models

Alibaba's Qwen Team has released research on Process Reward Models (PRMs) for mathematical reasoning. Their approach combines Monte Carlo estimation with LLM validation, potentially transforming how AI systems handle complex mathematical operations.

The team's breakthrough comes from their hybrid approach:

• They're using both Monte Carlo estimation AND LLM judgment to validate reasoning steps

• Their "consensus filtering" only keeps data when both methods agree (cutting noise by 60%!)

• They're focusing on step-by-step accuracy instead of just final answers

The 72B parameter model achieved 78.3% F1 score on PROCESSBENCH and superior performance compared to existing open-source alternatives.

Qwen's approach to mathematical reasoning could influence how we tackle other complex reasoning tasks in AI.

🍎 Apple Joins Consortium to Help Develop Next-Gen AI Data Center Tech

Apple has joined the Ultra Ethernet Consortium, a group dedicated to developing next-generation data center technologies optimized for AI and high-performance computing workloads.

This collaboration aims to enhance data center efficiency and performance, addressing the increasing demands of AI applications.

By participating in this consortium, Apple aligns with industry leaders to advance data center innovations that support the growing computational needs of AI technologies.

📱 New 8B LLM Outperforms GPT-4V in Visual Tasks While Running on Your Phone

OpenBMB has announced the release of MiniCPM-o 2.6: an 8-billion-parameter model that not only runs on smartphones but outperforms GPT-4V in visual processing tasks. 

What makes it special:

• Runs on consumer devices (yes, even your iPad)

• Handles vision, speech, and language processing

• Outperforms GPT-4V on visual tasks

• Processes high-res images up to 1.8M pixels

• Supports real-time video and audio processing

The model has a 70.2 average score on OpenCompass, surpassing GPT-4V in visual processing tasks.

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