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A team of AI researchers with Google’s DeepMind London group has found that certain large language models (LLMs) can serve as effective mediators between groups of people with differing viewpoints regarding a given topic. The work is published in the journal Science.

Over the past several decades, political divides have become common in many countries—most have been labeled as either liberal or conservative. The advent of the internet has served as fuel, allowing people from either side to promote their opinions to a wide audience, generating anger and frustration. Unfortunately, no tools have surfaced to diffuse the tension of such a political climate. In this new effort, the team at DeepMind suggests AI tools such as LLMs may fill that gap.

To find out if LLMs could serve as effective mediators, the researchers trained LLMs called Habermas Machines (HMs) to serve as caucus mediators. As part of their training, the LLMs were taught to identify areas of overlap between viewpoints of people in opposing groups—but not to try to change anyone’s opinions.

Could AGI be here by 2025? In a shocking new interview, Sam Altman — OpenAI’s CEO — just dropped some MAJOR revelations about their path to artificial general intelligence.

Unlike his usual careful corporate speak, Sam appears surprisingly confident about what’s ahead.

In this video, I break down Sam’s latest statements, OpenAI’s five-level roadmap to AGI, and why this matters for YOU.

After working full-time in AI since January 2023 and studying these developments closely, I’ll give you my analysis on:

Akash Systems has signed a non-binding preliminary memorandum of terms with the U.S. Department of Commerce for $18.2 million in direct funding and $50 million in federal and state tax credits through the CHIPS Act. Although this isn’t yet a binding contract that will give the company the promised funds, it’s an important first step in the negotiation process for the Oakland-based startup, which shows that both the company and the U.S. government are gradually moving towards a formal agreement. According to Akash Systems (h/t Axios), it will use the funds to ramp up its operations for producing diamond-cooled semiconductors for AI, data centers, space applications, and defense markets.

Diamond-cooling technology goes deeper than just thermal paste with nano-diamond technology. For example, some use synthetic diamonds as the chip substrate, utilizing the material’s thermal conductivity to more efficiently move heat away from the processor. So, let’s look closer at Akash’s solution.

Companies that own or operate critical infrastructure increasingly rely on artificial intelligence. Airports use A.I. in their security systems; water companies use it to predict pipe failures; and energy companies use it to project demand. On Thursday, the U.S. Department of Homeland Security will release new guidance for how such companies use the technology.

The document, a compilation of voluntary best practices, stems from an executive order that President Biden signed more than a year ago to create safeguards around A.I. Among other measures, it directed the Department of Homeland Security to create a board of experts from the private and public sectors to examine how best to protect critical infrastructure. The risks run the gamut from an airline meltdown to the exposure of confidential personal information.

Alejandro N. Mayorkas, the homeland security secretary, first convened the board in May. It includes Sam Altman, the chief executive of OpenAI; Jensen Huang, the chief executive of Nvidia; Sundar Pichai, the chief executive of Alphabet; and Vicki Hollub, the chief executive of Occidental Petroleum.

If you’ve recently scrolled through Instagram, you’ve probably noticed it: users posting AI-generated images of their lives or chuckling over a brutal feed roast by ChatGPT. What started as an innocent prompt – “Ask ChatGPT to draw what your life looks like based on what it knows about you” – has gone viral, inviting friends, followers, and even ChatGPT itself to get a peek into our most personal details. It’s fun, often eerily accurate, and, yes, a little unnerving.

The trend that started it all

A while ago, Instagram’s “Add Yours” sticker spurred the popular trend “Ask ChatGPT to roast your feed in one paragraph.” What followed were thousands of users clamouring to see the AI’s take on their profiles. ChatGPT didn’t disappoint – delivering razor-sharp observations on everything from overused vacation spots to the endless brunch photos and quirky captions, blending humour with a dash of truth. The playful roasting felt oddly familiar, almost like a best friend’s inside joke.

“The last two decades saw software transform nearly every industry, a trend famously captured by venture capitalist Marc Andreessen’s phrase ” software is eating the world.

Software became the backbone of industries like retail, transportation, finance, and entertainment, leading to a world where digital tools and applications are integral to daily life.

Looking forward, many experts believe that artificial intelligence (AI) will play a similarly transformative role over the next 20 years.

Non-invasive BCIs let you harness tech benefits and enhance cognition without implanting a brain chip.


The problem with conventional non-invasive BCIs is that they are not as accurate as invasive BCIs. They collect data using external sensors that are not in direct contact with brain tissues, and any disturbance in a user’s surroundings could affect their function.

According to the CMU researchers, AI-based deep neural networks can solve this problem. They are more advanced than artificial neural networks used for facial recognition, speech recognition, and various other simple tasks.

In the quest to uncover the fundamental particles and forces of nature, one of the critical challenges facing high-energy experiments at the Large Hadron Collider (LHC) is ensuring the quality of the vast amounts of data collected. To do this, data quality monitoring systems are in place for the various subdetectors of an experiment and they play an important role in checking the accuracy of the data.