Is AI All Hype?

Here is what’s new in the AI world.

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MIT Study Reveals Widespread Struggle to Monetize AI

A new study from MIT challenges the widespread enthusiasm for AI, revealing that a vast majority of companies are failing to see a financial return on their significant investments in the technology.

Dubbing this the "GenAI Divide," the research found that while 95% of organizations see no measurable profit impact, a small minority, just 5%, are successfully generating millions in value from their integrated AI projects.

The study, titled "The GenAI Divide: State of AI In Business 2025," notes that over 80% of businesses have experimented with tools like ChatGPT and Copilot, and nearly 40% have deployed them.

However, these tools are primarily boosting individual productivity rather than improving overall financial performance.

According to the research, the main reasons for failure are rigid workflows, an inability for AI to learn from its specific context, and a misalignment with daily operational needs.

The study identified four key patterns that define this divide:

The report concluded that the primary obstacle is not a lack of infrastructure, regulation, or talent, but a lack of learning, as most GenAI systems fail to adapt, retain feedback, or improve over time.

Furthermore, while GenAI adoption has not yet led to widespread job cuts, the top-performing companies are starting to see a selective impact on roles in customer support, software engineering, and administrative tasks.

These successful organizations also report measurable savings from reduced spending on business process outsourcing (BPO) and external agencies.

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Meituan Unveils Massive 560B Parameter LLM, Open-Sourced for Global Use

On September 1st, Chinese tech company Meituan launched its first open-source large language model (LLM), named LongCat-Flash-Chat.

The model has been made publicly available on platforms like GitHub and Hugging Face, representing Meituan's inaugural contribution to the global open-source AI community under its "Building LLM" initiative.

The model is distinguished by its Mixture-of-Experts (MoE) architecture, which features a massive 560 billion parameters. However, its innovative design ensures that for any given input, only a fraction of these parameters, between 18.6 billion and 31.3 billion, are used.

This selective activation approach allows the model to balance high performance with remarkable efficiency, enabling it to compete with leading models while being particularly effective for autonomous agent tasks.

To achieve this, Meituan incorporated several technical innovations, including a "Zero-Computation Experts" mechanism and a PID controller to maintain stable performance.

These features, along with cross-layer pathways, helped parallelize computation and reduce the training time to just 30 days.

The model's development leveraged advanced techniques like hyperparameter transfer and model stacking to ensure training stability. To boost its agent capabilities, Meituan created a custom evaluation dataset and used multi-agent methods to produce high-quality training data.

This release is a strategic part of Meituan's three-tiered AI strategy, which encompasses "AI at Work," "AI in Products," and the foundational "Building LLM" level.

It follows previous AI product launches, such as an AI coding agent and a business decision assistant.

By open-sourcing LongCat-Flash-Chat, Meituan aims to share its advancements in scalability, speed, and cost-effectiveness with the global developer community.

Tencent Beats AI Giants with Open-Source Translation Model

Chinese technology conglomerate Tencent Holdings unveiled a new open-source translation model on Monday, which excelled in an international machine-translation contest despite its relatively compact size.

The achievement underscores China’s continued advancements in artificial intelligence.

Preliminary results released by the organizer of the Tenth Conference on Machine Translation (WMT25) showed that Tencent’s Hunyuan-MT-7B model ranked first in 30 out of 31 test categories in the general machine-translation track.

WMT25 provides a venue for researchers and developers to present innovations in computer-assisted translation.

Although the model contains just 7 billion parameters, a common metric in AI where larger numbers typically correlate with stronger performance, it outperformed considerably bigger, proprietary models from rivals such as Google and OpenAI.

Tencent, headquartered in Shenzhen, attributed the model’s success to its comprehensive training framework, which incorporates meticulous dataset curation, continual pre-training, and multiple rounds of fine-tuning and reinforcement learning.

These techniques help refine the model for optimal output.

The competition evaluated English translations involving languages such as Arabic, Estonian, and Maasai, which is spoken by approximately 1.5 million people in Kenya and Tanzania.

Other language pairs included Czech-Ukrainian and Japanese–Simplified Chinese. The model did not rank first in English–Bhojpuri, a language used by about 50.5 million people in northern India and Nepal.

Tom Kocmi, a researcher at AI company Cohere and an organizer of WMT25, noted on LinkedIn that the preliminary rankings should be interpreted cautiously, as they relied on automated evaluation and could reflect certain biases.

The final official rankings, which incorporate human evaluation and detailed analysis, will be announced during the WMT25 conference in Suzhou, China, from November 5 to 9.

Tencent has already integrated the Hunyuan translation model into several of its in-house products, including Tencent Meeting, a web browser, and the enterprise edition of WeChat. The model is also available on open-source platforms Hugging Face and GitHub.

Elon Musk's xAI Sues Former Employee for Allegedly Stealing Grok Secrets for OpenAI

Elon Musk's artificial intelligence company, xAI, has filed a lawsuit in a California federal court against a former employee, Xuechen Li, accusing him of stealing trade secrets related to its Grok AI chatbot and sharing them with OpenAI.

According to the complaint, Li was part of a small, 20-person technical team at xAI since February 2023 and played a key role in developing Grok's AI models.

The company alleges that before resigning on July 28, Li copied confidential information from his work laptop to a personal storage device.

To conceal his actions, he reportedly deleted his browser history, altered system logs, and compressed and renamed files before transferring them.

xAI claims the stolen information includes advanced proprietary technology that gives Grok features superior to competitors like ChatGPT. The lawsuit states that this information could provide OpenAI with a "potential overwhelming edge" in the AI industry.

xAI confronted Li in a meeting on August 14, during which he allegedly admitted to the theft but tried to conceal its full extent. The company later discovered he had taken additional material beyond what he disclosed.

Li resigned shortly after liquidating approximately $7 billion in company shares and copying the confidential data. He was scheduled to begin working at OpenAI on August 19.

xAI is seeking a court order to block his employment there and is requesting unspecified monetary damages.

This legal action adds another layer to the ongoing conflict between Elon Musk and OpenAI, which he co-founded in 2015.

Musk has since become a vocal critic, suing OpenAI and Microsoft earlier this year, alleging they abandoned their original non-profit mission in pursuit of profit. OpenAI has countersued, accusing Musk of harassment.

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-Shen & Towards AGI team