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Brainsourcing automatically identifies human preferences

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Researchers at the University of Helsinki have developed a technique, using artificial intelligence, to analyse opinions, and draw conclusions using the brain activity of groups of people. This technique, which the researchers call "brainsourcing," can be used to classify images or recommend content, something that has not been demonstrated before. Crowdsourcing is a method to break up a more complex task into smaller tasks that can be distributed to large groups of people and solved individually. For example, people can be asked if an object can be seen in an image, and their responses are used as instructional data for an image recognition system. Even the most advanced image recognition systems based on artificial intelligence are not yet fully automated.


World's First Neuroprosthetic Uses AI, Human Control to Create Hand Movements

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It is a breakthrough moment for neuroprosthetics. A team of scientists from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland has combined human control and AI robotics to improve prosthetics' movements -- a world-first for this method of neural prosthetics. Their work was published in Nature Machine Intelligence in September. The formal term is neural prosthetics. These types of prosthetics stimulate a person's nervous system through electrical stimulation to make up for deficiencies that get in the way of general motor skills.


Graph Theory & Machine Learning in Neuroscience

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Graph theory is the study of graphs, mathematical structures that model the relationships between objects. In this example, we see a social network. A line represents a friendship between the people that it connects. In more technical terms, every person would be called a "node" or "vertex," while every line that connects would be called a "link" or "edge." So, this graph has 5 vertices and 7 edges.


DeepMind Explores Deep RL for Brain and Behaviour Research – IAM Network

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As a basis for modelling brain function, deep learning has in recent years been used to model systems in vision, audition, motor control, navigation, and cognitive control. In a new paper, DeepMind researchers call attention to another "fundamentally novel" development in AI research -- deep reinforcement learning (deep RL) -- which they believe also has vital implications for neuroscience and deserves more attention from neuroscientists. The first neuroscience applications of supervised deep learning can be traced back to the 1980s. The increasing availability of more powerful computers over the past decade has renewed research efforts in applying AI approaches -- especially supervised deep learning -- to neuroscience.Deep RL unites deep learning and reinforcement learning, a computational framework that has already had a substantial impact on neuroscience research. The DeepMind team proposes deep RL as a comprehensive framework for studying the interplay between learning, representation, and decision-making that can bring new set of research tools and a wide range of novel hypotheses to the brain sciences.Although deep neural networks have proven an impressive model for neural representation, the team notes that related research has mostly utilized supervised training and has therefore provided little direct leverage on the big-picture problem of understanding motivated, goal-directed …


Top industries AI is impacting in 2020

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Artificial Intelligence (AI) is changing the world. Many industries have already been impacted by the integration of AI technology to improve business processes, but that's only the beginning. Through the use of big data, machine learning, and the Internet of Things (IoT), AI captures the ability to think and make decisions like a human would -- but on a massive scale. Correspondingly, this technology has found a use in almost every sector of industry. Education, healthcare, human resources, marketing, and supply chain management have changed and continue to develop through the use of AI technology.


Is Elon Musk Capable Of Building Cyborgs? - Analytics India Magazine

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With the recent tweet on Neuralink, Elon Musk again hit the headlines this week where he stated that the company is going to update on the progress of this mysterious company in the coming month. In fact, the last major update came from this brain-machine interface company last year around the same time, where he spoke about the technology "threads," surpassing the traditional ones, which can be implanted in human brains to solve some of the brain disorders people are facing. He ultimately revealed his interest "to achieve a symbiosis with AI" by merging technology with human brains and not taking over. This raises a serious question -- can Elon Musk build cyborgs in the near future? SpaceX and Tesla CEO, Elon Musk has been known for bringing extraordinary ideas to life like electric cars, sending rockets to Mars, and creating solar cities, to name a few.


Elon Musk claims mysterious brain chip will be able to cure depression and addiction: 'It's both great and terrifying'

The Independent - Tech

Elon Musk has revealed more details about his mysterious brain-computer chip startup Neuralink, claiming that it could be used to help cure addiction and depression. Mr Musk founded Neuralink in 2016, though few details about how the technology will work have been revealed. After receiving more than $158m (£125m) in funding, Neuralink announced in a 2019 presentation that it had developed a "sewing machine-like" device capable of connecting brains directly to computers. More information about Neuralink will be revealed on 28 August, Mr Musk said on Thursday, prompting Twitter user Pranay Pathole to ask the billionaire entrepreneur what future capabilities could be expected. "Can Neuralink be used to retrain the part of the brain which is responsible for causing addiction or depression? It'd be great if Neuralink can be used for something like addiction/ depression," he asked.


Neuralink will share progress on linking human brains with AI next month

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Elon Musk's startup Neuralink says it will share progress next month on the company's mission to link human brains with AI. When Musk appeared on Joe Rogan's podcast in September 2018, the CEO told Rogan that Neuralink's long-term goal is to enable human brains to be "symbiotic with AI", adding that the company would have "something interesting to announce in a few months, that's at least an order of magnitude better than anything else; probably better than anyone thinks is possible". Neuralink held an event in San Francisco in July last year, during simpler times, where the company said it aims to insert electrodes into the brains of monkeys and humans to enable them to control computers. "Threads" which are covered in the electrodes are implanted in the brain near the neurons and synapses by a robot surgeon. These threads record the information being transmitted onto a sensor called the N1.


Elon Musk: Update to Neuralink computer-brain tech is coming soon

ZDNet

Elon Musk has said an update on the progress of his Neuralink implant devices, which connects a computer directly in to the brain, is coming next month. Neuralink aims to develop ultra-high bandwidth brain-computer interfaces, and in a tweet Musk said 28 August will see the first update to Neuralink since announcing the brain-machine interface project in 2017. When Musk revealed Neuralink, he hyped the technology as an answer to the threat of artificial intelligence, which he said presented an "existential risk" to humans. Last year, the company shed some light on what it's working on after updating its sparse website with a few details about job vacancies. Musk thinks his direct brain-to-machine interface -- or "neural lace" -- would help humans avoid becoming "house cats" to artificial intelligence.


Monkeying with the piano

Science

Neuroscience The anatomical organization of auditory cortical pathways in nonhuman primates (NHPs) shows remarkable similarities with humans. So why don't NHPs have a more speech-like communication system? Archakov et al. trained macaques to perform an auditory-motor task using a purpose-built piano. Mapping brain activity by functional magnetic resonance imaging showed that sound sequences activated the auditory midbrain and cortex. More importantly, sound sequences that had been learned by self-production also activated motor cortex and basal ganglia. This shows that monkeys can form auditory-motor links and that this is not the reason why they do not speak. Instead, the origin of speech in humans may have required the evolution of a command apparatus that controls the upper vocal tract. Proc. Natl. Acad. Sci. U.S.A. 117 , 15242 (2020).