🤖 This Computer Runs on Human Brain Cells

🧠 This Computer Runs on Human Brain Cells

🪧 Which Job Role Is Most Exposed to AI?

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Cortical Labs engineered “CL1,” the world’s first biological computer that fuses human brain cells with silicon hardware to create Synthetic Biological Intelligence (SBI), which leverages billions of years of human evolution to operate with unmatched energy efficiency.

It’s all powered by organoids: tiny, self-organized 3D tissue clusters lab-grown from human stem cells to mimic the structure and function of the human brain. To train “CL1,” Cortical Labs rewards these organoids with dopamine when they generate correct actions.

It successfully played DOOM, a first-person shooter video game where a space marine called Doomguy fights hordes of demons. To achieve this, Cortical Labs leveraged “FEP”: when organoids produce the desired action of slaying demons, they’re given localized electrical pulses.

Since the organoids are naturally inclined to minimize unpredictability, they physically restructure their synaptic connections to favor actions that lead to these localized electrical pulses. In simple terms, the organoids literally rewire themselves to become more efficient at processing DOOM’s data.

Playing DOOM isn’t about the video game itself. It’s proof that biological computers can receive the Game State (i.e., a current “snapshot” of the video game) and craft real-time strategies that adapt to the ever-changing gameplay dynamics.

This demo demonstrates the potential of utilizing human brain cells as a computing substrate, which may ultimately achieve 100,000,000x more energy efficiency than traditional silicon-based hardware at complex pattern recognition.

Anthropic introduced a new hybrid metric called “observed exposure,” which measures how frequently different sectors of the U.S. economy are actually employing AI to automate, not assist with, economically valuable tasks.

They discovered that computer programmers have the worst observed exposure at 74.5%. While computer programmers face the highest potential job loss, they’re not necessarily the ones losing their jobs right now. So, what the heck does that even mean? The 74.5% points to the “front door” of this career path closing.

The WEF estimates that about 170 million new jobs will be created this decade, while around 92 million old jobs will be displaced this decade. While these projections suggest the overall number of jobs will increase, it also means 22% of current job roles will disappear by 2030.

Unfortunately, it’s mostly targeted at entry-level employment opportunities. Since late 2022, there has been a 14% decrease in “job-finding rates” for U.S. workers aged 22 to 25.

These entry-level job roles were traditionally the on-ramp to successful careers in law, finance, and marketing. But AI can now perform detailed legal research and analyze market trends more accurately and more efficiently. In contrast, senior-level job roles are thriving, spending roughly 10% less time on routine, administrative work.

Anthropic CEO Dario Amodei forecasts a radical economic “decoupling”: a future where AI-driven productivity gains yield explosive annual GDP growth of up to 10%, while simultaneously driving unemployment levels as high as 20%. In simple terms, less human labor is needed to produce wealth because AI can automate multiple job roles.

City Detect raised a $13M Series A to help cities stay safe and clean.

Axiomatic AI closed an $18M Seed Round to tame mathematical rigor.

Nscale landed a $2B Series C for advanced superintelligence at scale.

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