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Category: information science – Page 284

Microsoft Invests $1 Billion to Create a World-Saving AI

Whether or not creating an AGI is even possible remains up for debate. Meanwhile, others may cringe at the thought of an AI with the intellect to match and exceed humanity. However, OpenAI has been bullish on the prospect. The company points to the breakthroughs researchers have made in last decade in getting AI algorithms to recognize images, translate languages, and control robots. One of OpenAI’s own AI projects can write fiction like a human can (sort of).

However, creating new AI-based technologies costs a lot of money. Not only does it require programming, but also renting access to thousands of servers. So OpenAI has been seeking funding. “The most obvious way to cover costs is to build a product, but that would mean changing our focus. Instead, we intend to license some of our pre-AGI technologies, with Microsoft becoming our preferred partner for commercializing them,” Altman wrote in a separate blog post.

  • The AI Breakthrough Will Require Researchers Burying Their Hatchets.

The First Complete Brain Wiring Diagram of Any Species Is Here

For a humble, microscopic worm with only 302 neurons, C. elegans has had a lot of firsts. It was the first multicellular animal to have its whole genome sequenced. It was also the spark that lit the connectome fire—the revolutionary idea that mapping the entirety of connections among neurons will unveil secrets of our minds, memory, and consciousness. And if the connectomists are to be believed, a map of individual brains may be the blueprint that will one day hurtle AI into human-level intelligence, or reconstruct an entire human mind in digital form.

More than 30 years ago, a pioneering group of scientists painstakingly traced and reconstructed the roundworm’s neural wiring by hand. The “heroic” effort, unaided by modern computers and brain-mapping algorithms, resulted in the first connectome in 1986.

Yet the “mind of the worm” map had significant lapses. For one, it only focused on one sex, the hermaphrodite—a “female” equivalent that can self-fertilize. This makes it hard to tell which connections are universal for the species, and which are dependent on sex and reproduction. For another, because the effort relied entirely on human beings who get tired, bored, and mess up, the map wasn’t entirely accurate. Even with multiple rounds of subsequent refinements, errors could linger, which would royally screw up any interpretation of results using these maps.

Australian Researchers Have Just Released The World’s First AI-Developed Vaccine

A team at Flinders University in South Australia has developed a new vaccine believed to be the first human drug in the world to be completely designed by artificial intelligence (AI).

While drugs have been designed using computers before, this vaccine went one step further being independently created by an AI program called SAM (Search Algorithm for Ligands).

Flinders University Professor Nikolai Petrovsky who led the development told Business Insider Australia its name is derived from what it was tasked to do: search the universe for all conceivable compounds to find a good human drug (also called a ligand).

Towards reconstructing intelligible speech from the human auditory cortex

Auditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combined the recent advances in deep learning with the latest innovations in speech synthesis technologies to reconstruct closed-set intelligible speech from the human auditory cortex. We investigated the dependence of reconstruction accuracy on linear and nonlinear (deep neural network) regression methods and the acoustic representation that is used as the target of reconstruction, including auditory spectrogram and speech synthesis parameters. In addition, we compared the reconstruction accuracy from low and high neural frequency ranges. Our results show that a deep neural network model that directly estimates the parameters of a speech synthesizer from all neural frequencies achieves the highest subjective and objective scores on a digit recognition task, improving the intelligibility by 65% over the baseline method which used linear regression to reconstruct the auditory spectrogram. These results demonstrate the efficacy of deep learning and speech synthesis algorithms for designing the next generation of speech BCI systems, which not only can restore communications for paralyzed patients but also have the potential to transform human-computer interaction technologies.

Researchers’ deep learning algorithm solves Rubik’s Cube faster than any human

Since its invention by a Hungarian architect in 1974, the Rubik’s Cube has furrowed the brows of many who have tried to solve it, but the 3D logic puzzle is no match for an artificial intelligence system created by researchers at the University of California, Irvine.

DeepCubeA, a learning algorithm programmed by UCI scientists and mathematicians, can find the solution in a fraction of a second, without any specific domain knowledge or in-game coaching from humans. This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state—each of six sides displaying a solid color—which apparently can’t be found through random moves.

For a study published today in Nature Machine Intelligence, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the to the goal state about 60 percent of the time. The algorithm also works on other combinatorial games such as the sliding tile , Lights Out and Sokoban.

Artificial Intelligence: A History

What Is Big Data? & How Big Data Is Changing The World! https://www.facebook.com/singularityprosperity/videos/439181406563439/

In this video, we’ll be discussing big data – more specifically, what big data is, the exponential rate of growth of data, how we can utilize the vast quantities of data being generated as well as the implications of linked data on big data.

[0:30–7:50] — Starting off we’ll look at, how data has been used as a tool from the origins of human evolution, starting at the hunter-gatherer age and leading up to the present information age. Afterwards, we’ll look into many statistics demonstrating the exponential rate of growth and future growth of data.

[7:50–18:55] — Following that we’ll discuss, what exactly big data is and delving deeper into the types of data, structured and unstructured and how they will be analyzed both by humans and machine learning (AI).

Neuroscience and artificial intelligence can help improve each other

Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don’t have much to do with real brain science. I’m a professor of bioengineering and neurosciences interested in understanding how the brain works as a system – and how we can use that knowledge to design and engineer new machine learning models.

In recent decades, brain researchers have learned a huge amount about the physical connections in the brain and about how the nervous system routes information and processes it. But there is still a vast amount yet to be discovered.

At the same time, computer algorithms, software and hardware advances have brought machine learning to previously unimagined levels of achievement. I and other researchers in the field, including a number of its leaders, have a growing sense that finding out more about how the brain processes information could help programmers translate the concepts of thinking from the wet and squishy world of biology into all-new forms of machine learning in the digital world.

This Brain Implant Could Change Lives

It sounds like science fiction: a device that can reconnect a paralyzed person’s brain to his or her body. But that’s exactly what the experimental NeuroLife system does. Developed by Battelle and Ohio State University, NeuroLife uses a brain implant, an algorithm and an electrode sleeve to give paralysis patients back control of their limbs. For Ian Burkhart, NeuroLife’s first test subject, the implications could be life-changing.

Featured in this episode:

Batelle:
https://www.battelle.org/

Ohio State University
https://wexnermedical.osu.edu/

Producer and Editor — Alan Jeffries
Camera — Zach Frankart, Alan Jeffries
Sound Recordist — Brandon MacLean
Graphics — Sylvia Yang
Animators — Ricardo Mendes, James Hazael, Andrew Embury.
Sound Mix and Design — Cadell Cook.

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