Brevan Howard does a significant amount of its crypto trading from the United Arab Emirates because of the country’s “sensible regulations,” an executive from the hedge fund told the AIM conference in Dubai on Monday.

“The regulators in the UAE are hard, but they want the industry to fly and so they write sensible regulations and they are prepared to talk to the industry in order to evolve those regulations,” Ryan Taylor, group head of compliance at hedge fund Brevan Howard, said during a panel on hedge fund trends and strategies.

Taylor said that Brevan Howard’s crypto trading operations represented about $2 billion of the firm’s total strategies which he said were over $30 billion. Beyond saying the UAE’s share of trading was significant, he did not give any precise indication.

“We’re also seeing new opportunities, such as those that are happening here in the UAE, whether it’s from the equity market or other opportunities, and we’re all excited about that,” Brandon Robinson, deputy head of private markets at JPMorgan Asset Management, said during the same debate.

Robinson, who oversees a department at JPMorgan that invests in some hedge funds, said the bank was talking to several managers in the area.

“The growth has been unprecedented. We thought the growth was up last year. It’s been just the same again,” said Jonathan Beardall, head of wealth and asset management at the Dubai International Financial Centre Authority (DIFC).

Dubai has 65 hedge funds registered in the city centre and that number would increase to 70 in the next few weeks, Beardall said.

Hedge funds trading on macro economics were up 3.6% for the year to the end of September, compared with the same period last year, hedge fund research firm Pivotal Path found.

Facebook owner Meta said on Friday it was releasing a batch of new AI models from its research division, including a “Self-Taught Evaluator” that may offer a path toward less human involvement in the AI development process.

The release follows Meta’s introduction of the tool in an August paper, which detailed how it relies upon the same “chain of thought” technique used by OpenAI’s recently released o1 models to get it to make reliable judgments about models’ responses.

That technique involves breaking down complex problems into smaller logical steps and appears to improve the accuracy of responses to challenging problems in subjects like science, coding, and math.

Meta’s researchers used entirely AI-generated data to train the evaluator model, eliminating human input at that stage as well.

The ability to use AI to evaluate AI reliably offers a glimpse at a possible pathway toward building autonomous AI agents that can learn from their own mistakes, two of the Meta researchers behind the project told Reuters.

Many in the AI field envision such agents as digital assistants intelligent enough to carry out a vast array of tasks without human intervention.

Self-improving models could cut out the need for an often expensive and inefficient process used today called Reinforcement Learning from Human Feedback, which requires input from human annotators who must have specialized expertise to label data accurately and verify that answers to complex math and writing queries are correct.

“We hope, as AI becomes more and more super-human, that it will get better and better at checking its work so that it will be better than the average human,” said Jason Weston, one of the researchers.

“The idea of being self-taught and able to self-evaluate is crucial to the idea of getting to this sort of super-human level of AI,” he said.

Other companies including Google and Anthropic have also published research on the concept of RLAIF, or Reinforcement Learning from AI Feedback. Unlike Meta, however, those companies tend not to release their models for public use.

Other AI tools released by Meta on Friday included an update to the company’s image-identification Segment Anything model, a tool that speeds up LLM response generation times and datasets that can be used to aid the discovery of new inorganic materials.

Honeywell has signed a deal with Google to connect artificial intelligence technology with its industrial data, both companies said on Monday, with a view to offering streamlined autonomous operations for its customers.

The partnership will bring together Alphabet-owned Google’s Gemini – its most advanced AI technology – and Honeywell’s industrial data collected through its Forge platform to automate tasks and reduce project times, in an industry that continues to grapple with a labor shortage.

The AI-powered tools will help automate tasks for engineers, warehouse workers, and technicians, among other uses, with the first AI-enabled solutions reaching Honeywell’s customers in 2025.

“The path to autonomy requires assets working harder, people working smarter and processes working more efficiently,” Vimal Kapur, chairman and CEO of Honeywell, said in a statement.

With the new AI-powered agent built on Google’s Vertex AI platform, automated tasks will lead to reduced project design cycles, Honeywell said, adding that users will be able to process various data types such as images, videos, text and sensor readings.

Honeywell, attempting to leverage the latest boom in AI technology, said it is aiming to reduce maintenance costs, increase operational productivity and “upskill employees” through the partnership with its customers.