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Your Cortex Contains 17 Billion Computers

Neural networks of neural networks.


Brains receive input from the outside world, their neurons do something to that input, and create an output. That output may be a thought (I want curry for dinner); it may be an action (make curry); it may be a change in mood (yay curry!). Whatever the output, that “something” is a transformation of some form of input (a menu) to output (“chicken dansak, please”). And if we think of a brain as a device that transforms inputs to outputs then, inexorably, the computer becomes our analogy of choice.

For some this analogy is merely a useful rhetorical device; for others it is a serious idea. But the brain isn’t a computer. Each neuron is a computer. Your cortex contains 17 billion computers.

Cancer can be precisely diagnosed using a urine test with artificial intelligence

Prostate cancer is one of the most common cancers among men. Patients are determined to have prostate cancer primarily based on PSA, a cancer factor in blood. However, as diagnostic accuracy is as low as 30%, a considerable number of patients undergo additional invasive biopsy and thus suffer from resultant side effects, such as bleeding and pain.

The Korea Institute of Science and Technology (KIST) announced that the collaborative research team led by Dr. Kwan Hyi Lee from the Biomaterials Research Center and Professor In Gab Jeong from Asan Medical Center developed a technique for diagnosing from within only 20 minutes with almost 100% accuracy. The research team developed this technique by introducing a smart AI analysis method to an electrical-signal-based ultrasensitive biosensor.

As a noninvasive method, a using urine is convenient for patients and does not need invasive biopsy, thereby diagnosing without side effects. However, as the concentration of cancer factors is low in urine, urine-based biosensors are only used for classifying risk groups rather than for precise diagnosis thus far.

Impulse neuro controller reduces PC gaming reaction times

Brink Bionics completed a very successful [Indiegogo](https://www.indiegogo.com/projects/impulse-neuro-controller-for-pc-gaming#/) crowdfunding campaign in 2020 and gained the confidence to [take part in the CES](https://twitter.com/BrinkBionics/status/1349458342087954433) just last week. The Waterloo, Canada-based startup has a single signature product for now, the Brink Bionics Impulse. It is described as a * neuro-controller for PC gaming, *and takes the form of a glove that uses built-in sensors to read your muscle bio-signals and applies AI to accurately predict your clicking intentions. They key claim for the product is that it can improve your gaming reaction speeds by as much as 80ms. Thus, the Impulse could be a boon to FPS, MOBA and RTS gamers on PC.


ToughDesk 500L RGB Battlestation is said to be a good choice for multi-monitor setups.

HEXUS® is a registered trademark.

Artificial intelligence researchers rank the top A.I. labs worldwide

LONDON — Artificial intelligence researchers don’t like it when you ask them to name the top AI labs in the world, possibly because it’s so hard to answer.

There are some obvious contenders when it comes to commercial AI labs. U.S. Big Tech — Google, Facebook, Amazon, Apple and Microsoft — have all set up dedicated AI labs over the last decade. There’s also DeepMind, which is owned by Google parent company Alphabet, and OpenAI, which counts Elon Musk as a founding investor.


DeepMind, OpenAI, and Facebook AI Research are fighting it out to be the top AI research lab in the world.

Designing customized ‘brains’ for robots

Contemporary robots can move quickly. “The motors are fast, and they’re powerful,” says Sabrina Neuman.

Yet in complex situations, like interactions with people, robots often don’t move quickly. “The hang up is what’s going on in the robot’s head,” she adds.

Perceiving stimuli and calculating a response takes a “boatload of computation,” which limits , says Neuman, who recently graduated with a Ph.D. from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Neuman has found a way to fight this mismatch between a robot’s “mind” and body. The method, called robomorphic computing, uses a robot’s physical layout and intended applications to generate a customized computer that minimizes the robot’s response time.

New approach to AI offers more certainty in the face of uncertainty

A new method to reason about uncertainty might help artificial intelligence to find safer options faster, for example in self-driving cars, according to a new study to be published shortly in AAAI involving researchers at Radboud University, the University of Austin, the University of California, Berkeley, and the Eindhoven University of Technology.

The researchers have defined a new approach to so-called ‘uncertain partially observable Markov decision processes, or uPOMDPs. In layman’s terms, these are models of the real world that estimate the probability of events. A car, for example, will face many unknown situations when it starts driving. To validate the of self-driving cars, extensive calculations are run to analyze how the AI would approach various situations. The researchers argue that with their new approach, these modeling exercises can become far more realistic, and thus allows AI to make better, safer decisions quicker.

#54: The End of Jobs, with Jeff Wald

Author and entrepreneur Jeff Wald discusses his book “The End of Jobs: The Rise of On-Demand Workers and The Agile Corporation,” on the latest Seeking Delphi™ podcast. The conclusions may not be what you anticipate from the title…


There’s a lot of automation that can happen that isn’t a replacement of humans but of mind-numbing behavior.” –Stewart Butterworth

Automation is going to cause unemployment, and we better prepare for it.”–Mark Cuban

In an early standup routine, Woody Allen once joked that when his father came home to announce that his job on an assembly line was replaced by a 50-dollar part, what was really disturbing was that his mother immediately ran out and bought one of those parts. As funny as that may be, the potential loss of millions of jobs to automation is no joking matter. The fears of such abound as automation, robotics and artificial intelligence continue to invade the world of work. But the scenarios for the future of human employment may be far more nuanced than you might expect. In this episode of Seeking Delphi™ entrepreneur and author Jeff Wald discusses his view of the future of work, as outlined in his book The End of Jobs: The Rise of On-demand Workers and the Agile Corporation. You can subscribe to Seeking Delphi™ on Apple podcasts, PlayerFM, MyTuner, Listen Notes, and YouTube. You can also follow us on twitter @Seeking_Delphi and Facebook.

Superintelligent AI May Be Impossible to Control; That’s the Good News

It may be theoretically impossible for humans to control a superintelligent AI, a new study finds. Worse still, the research also quashes any hope for detecting such an unstoppable AI when it’s on the verge of being created.

Slightly less grim is the timetable. By at least one estimate, many decades lie ahead before any such existential computational reckoning could be in the cards for humanity.

Alongside news of AI besting humans at games such as chess, Go and Jeopardy have come fears that superintelligent machines smarter than the best human minds might one day run amok. “The question about whether superintelligence could be controlled if created is quite old,” says study lead author Manuel Alfonseca, a computer scientist at the Autonomous University of Madrid. “It goes back at least to Asimov’s First Law of Robotics, in the 1940s.”