AI Research
They created a 100% functional human mind, it has AI and answers millions of questions like a human
In the race to develop artificial general intelligence (AGI), companies like OpenAI and Meta are investing billions of dollars in systems capable of replicating human thought.
Although there is still no single, accepted definition for AGI, the concept aims to build an artificial intelligence so versatile that it can tackle multiple tasks similarly to a person.
And while current AI has demonstrated amazing abilities—such as beating chess champions or predicting protein structures—it is still far from matching the human mind in terms of reasoning and general behavior.
However, an international team of scientists has developed a new system called Centaur, which could bring us a little closer to that goal. The project, led by cognitive scientist Marcel Binz of the Helmholtz Research Center in Munich, seeks to explore whether a language model similar to ChatGPT can behave like a human in psychological experiments.
The system, named after the mythological half-human, half-horse creature, was trained to replicate the decisions and behaviors of real volunteers in more than 160 psychological studies.
These experiments, compiled by Binz and his team, included tasks as diverse as memorizing words, playing slot machines, or piloting a virtual spaceship to find treasure.
Unlike traditional models, which typically focus on a single skill, Centaur was designed to generalize human behaviors across multiple contexts. “We wanted to see if it was possible to mimic different mental functions in a single model, without having to design a theory from scratch for each task,” Binz explained.
To achieve this, the researchers used the open-source LLaMA model created by Meta, which allows fine-tuning of its internal workings. They fed the system more than 10 million human responses and rewarded it whenever its choices aligned with those of real participants.
The result was a model that not only mimicked response patterns but also displayed human-like reasoning in new situations.
One of the most notable aspects of the experiment was Centaur’s knowledge transfer capabilities. When presented with new versions of the games—such as replacing the spaceship with a flying carpet—the model retained the original search strategy, just as a person would.
Furthermore, when asked to solve logic problems not included in its training, Centaur replicated not only human successes but also their most common errors.
This performance sparked the interest of several experts. Russ Poldrack, a cognitive scientist at Stanford University, called the model “impressive” and asserted that it is the first to replicate so many tasks with such fidelity to human behavior. Another specialist, Ilia Sucholutsky of New York University, emphasized that Centaur significantly outperforms traditional cognitive models.
However, criticism also arose. Olivia Guest of Radboud University in the Netherlands questioned the fact that Centaur is not based on a concrete theory of mind. “Making predictions is not the same as understanding how the mind works,” she noted.
A similar opinion was expressed by Gary Lupyan of the University of Wisconsin-Madison, who asserted that the goal of cognitive science is not to replicate behaviors, but rather to understand the mechanisms that generate them.
Binz acknowledges these limitations. According to him, Centaur is not intended to be a definitive theory of human thought, but it can serve as a platform for creating new hypotheses and exploring how certain cognitive patterns emerge. His team is currently working on increasing the experimental database fivefold to further expand the model’s capabilities.
As artificial intelligence advances by leaps and bounds, systems like Centaur open a fascinating door: using AI not just as a tool, but as a mirror to better understand the human mind. Although there is still a long way to go toward true AI, each step like this allows us to see more clearly what makes us human.
AI Research
Now Artificial Intelligence (AI) for smarter prison surveillance in West Bengal – The CSR Journal
OpenAI CEO Sam Altman walks on the day of a meeting of the White House Task Force on Artificial Intelligence (AI) Education in the East Room at the White House in Washington, D.C., U.S., September 4, 2025.
Brian Snyder | Reuters
OpenAI has sharply raised its projected cash burn through 2029 to $115 billion as it ramps up spending to power the artificial intelligence behind its popular ChatGPT chatbot, The Information reported on Friday.
The new forecast is $80 billion higher than the company previously expected, the news outlet said, without citing a source for the report.
OpenAI, which has become one of the world’s biggest renters of cloud servers, projects it will burn more than $8 billion this year, some $1.5 billion higher than its projection from earlier this year, the report said.
The company did not immediately respond to Reuters request for comment.
To control its soaring costs, OpenAI will seek to develop its own data center server chips and facilities to power its technology, The Information said.
OpenAI is set to produce its first artificial intelligence chip next year in partnership with U.S. semiconductor giant Broadcom, the Financial Times reported on Thursday, saying OpenAI plans to use the chip internally rather than make it available to customers.
The company deepened its tie-up with Oracle in July with a planned 4.5-gigawatts of data center capacity, building on its Stargate initiative, a project of up to $500 billion and 10 gigawatts that includes Japanese technology investor SoftBank. OpenAI has also added Alphabet’s Google Cloud among its suppliers for computing capacity.
The company’s cash burn will more than double to over $17 billion next year, $10 billion higher than OpenAI’s earlier projection, with a burn of $35 billion in 2027 and $45 billion in 2028, The Information said.
AI Research
Who is Shawn Shen? The Cambridge alumnus and ex-Meta scientist offering $2M to poach AI researchers
Shawn Shen, co-founder and Chief Executive Officer of the artificial intelligence (AI) startup Memories.ai, has made headlines for offering compensation packages worth up to $2 million to attract researchers from top technology companies. In a recent interview with Business Insider, Shen explained that many scientists are leaving Meta, the parent company of Facebook, due to constant reorganisations and shifting priorities.“Meta is constantly doing reorganizations. Your manager and your goals can change every few months. For some researchers, it can be really frustrating and feel like a waste of time,” Shen told Business Insider, adding that this is a key reason why researchers are seeking roles at startups. He also cited Meta Chief Executive Officer Mark Zuckerberg’s philosophy that “the biggest risk is not taking any risks” as a motivation for his own move into entrepreneurship.With Memories.ai, a company developing AI capable of understanding and remembering visual data, Shen is aiming to build a niche team of elite researchers. His company has already recruited Chi-Hao Wu, a former Meta research scientist, as Chief AI Officer, and is in talks with other researchers from Meta’s Superintelligence Lab as well as Google DeepMind.
From full scholarships to Cambridge classrooms
Shen’s academic journey is rooted in engineering, supported consistently by merit-based scholarships. He studied at Dulwich College from 2013 to 2016 on a full scholarship, completing his A-Level qualifications.He then pursued higher education at the University of Cambridge, where he was awarded full scholarships throughout. Shen earned a Bachelor of Arts (BA) in Engineering (2016–2019), followed by a Master of Engineering (MEng) at Trinity College (2019–2020). He later continued at Cambridge as a Meta PhD Fellow, completing his Doctor of Philosophy (PhD) in Engineering between 2020 and 2023.
Early career: Internships in finance and research
Alongside his academic pursuits, Shen gained early experience through internships and analyst roles in finance. He worked as a Quantitative Research Summer Analyst at Killik & Co in London (2017) and as an Investment Banking Summer Analyst at Morgan Stanley in Shanghai (2018).Shen also interned as a Research Scientist at the Computational and Biological Learning Lab at the University of Cambridge (2019), building the foundations for his transition into advanced AI research.
From Meta’s Reality Labs to academia
After completing his PhD, Shen joined Meta (Reality Labs Research) in Redmond, Washington, as a Research Scientist (2022–2024). His time at Meta exposed him to cutting-edge work in generative AI, but also to the frustrations of frequent corporate restructuring. This experience eventually drove him toward building his own company.In April 2024, Shen began his academic career as an Assistant Professor at the University of Bristol, before launching Memories.ai in October 2024.
Betting on talent with $2M offers
Explaining his company’s aggressive hiring packages, Shen told Business Insider: “It’s because of the talent war that was started by Mark Zuckerberg. I used to work at Meta, and I speak with my former colleagues often about this. When I heard about their compensation packages, I was shocked — it’s really in the tens of millions range. But it shows that in this age, AI researchers who make the best models and stand at the frontier of technology are really worth this amount of money.”Shen noted that Memories.ai is looking to recruit three to five researchers in the next six months, followed by up to ten more within a year. The company is prioritising individuals willing to take a mix of equity and cash, with Shen emphasising that these recruits would be treated as founding members rather than employees.By betting heavily on talent, Shen believes Memories.ai will be in a strong position to secure additional funding and establish itself in the competitive AI landscape.His bold $2 million offers may raise eyebrows, but they also underline a larger truth: in today’s technology race, the fiercest competition is not for customers or capital, it’s for talent.
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