Lifeboat Foundation

Can we ever reverse-engineer our thinking? This is one of the questions addressed in my new cinematic documentary Consciousness: Evolution of the Mind making a splash around the world. The film is now available for viewing on demand on Vimeo, Plex, Tubi, Social Club TV and other global networks with its worldwide premiere aired on June 8, 2021. This is my take on the nature of consciousness and reverse engineering of our mental faculties in order to create AGI. Enjoy!

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Honda may have dragged its feet for years when it came to electric two-wheelers, but the company has now released a number of new and interesting designs. The latest is the ultra-affordable Honda U-GO electric scooter.

Honda launched the U-GO through its Chinese arm Wuyang-Honda as a follow-up to its other low-cost Chinese electric scooters designed purely for urban riding.

The company announced two versions of the U-GO with different speeds and power levels.

Transformer-based deep learning models like GPT-3 have been getting much attention in the machine learning world. These models excel at understanding semantic relationships, and they have contributed to large improvements in Microsoft Bing’s search experience. However, these models can fail to capture more nuanced relationships between query and document terms beyond pure semantics.

The Microsoft team of researchers developed a neural network with 135 billion parameters, which is the largest “universal” artificial intelligence that they have running in production. The large number of parameters makes this one of the most sophisticated AI models ever detailed publicly to date. OpenAI’s GPT-3 natural language processing model has 175 billion parameters and remains as the world’s largest neural network built to date.

Microsoft researchers are calling their latest AI project MEB (Make Every Feature Binary). The 135-billion parameter machine is built to analyze queries that Bing users enter. It then helps identify the most relevant pages from around the web with a set of other machine learning algorithms included in its functionality, and without performing tasks entirely on its own.

Stanford is looking to democratize research on artificial intelligence and medicine by releasing the world’s largest free repository of AI-ready annotated medical imaging datasets. This will allow people from all over the world to access specific data that they need for their respective projects, which could lead to potentially life-saving breakthroughs in these fields.

The use of artificial intelligence in medicine is becoming increasingly pervasive. From analyzing tumors to detecting a person’s pumping heart, AI looks like it will have an important role for the near future.

The AI-powered devices, which can rival the accuracy of human doctors in diagnosing diseases and illnesses, have been making strides as well. These systems not only spot a likely tumor or bone fracture but also predict the course of an illness with some reliability for recommendations on what to do next. However, these systems require expensive datasets that are created by humans who annotate images meticulously before handing them over to compute power, so they’re rather costly either way you look at it given their price tags–millions even if your data is purchased from others or millions more if one has created their own dataset painstakingly through careful annotation of images such as CT scans and x-rays along with MRI’s etcetera depending upon how advanced each system needs be.

Bear Flag Robotics, a developer of autonomous driving technology for tractors, is being acquired by John Deere for $250 million.

Let’s face it. Software has holes. And hackers love to exploit them. New vulnerabilities appear almost daily. If you have software — we all do — you need to keep tabs on the latest vulnerabilities.

A new article in Science magazine gives an overview of almost three decades of research into colloidal quantum dots, assesses the technological progress for these nanometer-sized specs of semiconductor matter, and weighs the remaining challenges on the path to widespread commercialization for this promising technology with applications in everything from TVs to highly efficient sunlight collectors.

“Thirty years ago, these structures were just a subject of scientific curiosity studied by a small group of enthusiasts. Over the years, quantum dots have become industrial-grade materials exploited in a range of traditional and emerging technologies, some of which have already found their way into commercial markets,” said Victor I. Klimov, a coauthor of the paper and leader of the team conducting quantum dot research at Los Alamos National Laboratory.

Many advances described in the Science article originated at Los Alamos, including the first demonstration of colloidal quantum dot lasing, the discovery of carrier multiplication, pioneering research into quantum dot light emitting diodes (LEDs) and luminescent solar concentrators, and recent studies of single-dot quantum emitters.

The physicians group identified the use of the chemicals in at least 1200 wells in six states, not including Pennsylvania.

The Inquirer’s editorial board identified the use of PFAS in eight fracking wells. Only the Pennsylvania Department of Environmental Protection can shed light on the full scope.

It’s interesting, but the most advanced robots are acrobatic enough. The Glaring Challenge in robotics right now is copying and duplicating the function of the Human Hand.

Researchers studying rodents’ leaping abilities suggest findings could help them create nimble artificial intelligence systems.