Cognitive Science


Wave Computing Unveils New Licensable 64-Bit AI IP Platform to Enable High-Speed Inferencing and Training in Edge Applications

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Wave Computing, the Silicon Valley company accelerating artificial intelligence (AI) from the datacenter to the edge, announced its new TritonAI 64 platform, which integrates a triad of powerful technologies into a single, future-proof intellectual property (IP) licensable solution. Wave's TritonAI 64 platform delivers 8-to-32-bit integer-based support for high-performance AI inferencing at the edge now, with bfloat16 and 32-bit floating point-based support for edge training in the future. Wave's TritonAI 64 platform is an industry-first solution, enabling customers the ability to address a broad range of AI use cases with a single platform. The platform delivers efficient edge inferencing and training performance to support today's AI algorithms, while providing customers with flexibility to future-proof their investment for emerging AI algorithms. Features of the TritonAI 64 platform include a leading-edge MIPS 64-bit SIMD engine that is integrated with Wave's unique approach to dataflow and tensor-based configurable technology.


#016 CNN Network in Network - 1x1 Convolutions Master Data Science 13.11.2018

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More generally, if we have not just one filter but multiple filters, then it's as if we have not just one unit but multiple units that are taking as inputs all the numbers in one slice, and then building them up into an output there the \(6\times 6\times number \enspace of \enspace filters \). One way to think about the \(1\times 1 \) convolution is that it is basically like having a fully connected neural network that applies to each of the \(36 \) different positions. What this fully connected neural network does, it has a \(32 \) dimensional input whereas the number of outputs equals the number of \(1\times 1 \) filters applied. Doing this every \(36 \) positions we end up with an output that is \(6\times 6 \times number \enspace of \enspace filters \). This can carry out a pretty non-trivial computation on our input volume.


US government is funding research into technology that will connect soldiers' brains to computers

Daily Mail - Science & tech

The Defense Advanced Research Projects Agency (DARPA) is funding research that could give a future generation of soldiers the power to control machines and weapons with their minds. The agency said it will fund six organizations through the Next-Generation Nonsurgical Neurotechnology (N3) program who will work to design and build interfaces for application in the U.S. military, that could be worn be soldiers and translate their brain signals into instructions. Those instructions could be used to control swarms of unmanned aerial vehicles, wield cyber defense systems, or facilitate military communications. Soldiers may be able to control vehicles and more by using only their minds under a new initiative from the U.S. Department of Defense. While the feat may sound firmly in the realm of science fiction, according to DARPA it is setting a completion date within four years.


North Korea calls Biden 'fool of low IQ' over Kim criticism

FOX News

SEOUL, South Korea – North Korea has labeled Joe Biden a "fool of low IQ" and an "imbecile bereft of elementary quality as a human being" after the Democratic presidential hopeful during a recent speech called North Korean leader Kim Jong Un a tyrant. Pyongyang's official Korean Central News Agency on Wednesday accused Biden of insulting the country's supreme leadership and committing an "intolerable and serious politically-motivated provocation" against the North. Biden during a campaign launch in Philadelphia on Saturday accused President Donald Trump of cozying up to "dictators and tyrants" like Kim and Russian President Vladimir Putin.


Everyone Is Talking About AI--But Do They Mean the Same Thing? - Liwaiwai

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In 2017, artificial intelligence attracted $12 billion of VC investment. We are only beginning to discover the usefulness of AI applications. Amazon recently unveiled a brick-and-mortar grocery store that has successfully supplanted cashiers and checkout lines with computer vision, sensors, and deep learning. Between the investment, the press coverage, and the dramatic innovation, "AI" has become a hot buzzword. But does it even exist yet?


What is Cognitive Computing? How are Enterprises benefitting from Cognitive Technology?

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AI has truly been a far-flung goal ever since the conception of computing, and every day we seem to be getting closer and closer to that goal with new cognitive computing models. Coming from the amalgamation of cognitive science and based on the basic premise of simulating the human thought process, the concept, as well as applications of cognitive computing, are bound to have far-reaching impacts on not just our private lives, but also industries like healthcare, insurance and more. The advantages of cognitive technology are well and truly a step beyond the conventional AI systems. According to David Kenny, General Manager, IBM Watson -- the most advanced cognitive computing framework, "AI can only be as smart as the people teaching it." The same is not true for the latest cognitive revolution.


AI is coming. How can it optimize internal logistics? - All Things Supply Chain

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Last week in the USA alone, 18.4 million people watched the penultimate "Game of Thrones" episode which was a record audience for the show. Although, I'm sure that the last episode yesterday even beat those numbers (I have not seen it yet, so no spoilers ahead!). One thing that made the series especially intriguing for viewers was the element of surprise or uncertainty, which made the unfolding of the story very unique compared to today's usual tv experience. Whether it's the sudden death of beloved characters, a completely unexpected change of heart or the failure of a supposed secret weapon at the decisive moment – Westeros is the land of uncertainty. If there were any internal logistics managers watching the series, I'm sure they felt a sense of familiarity, since their job is characterized by unpredictability that it is Game of Thrones twice over, day after day.


6 Simple Ways to Use Neuroscience to Increase Marketing Productivity

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Neuroscience is a multidisciplinary science that is concerned with the study of the structure and function of the nervous system. When applied to our professional lives, neuroscience can help us to unlock our greatest potential. Increasing your meaningful productivity can have a huge impact on your day-to-day work and can greatly influence your professional success over a long period of time. This week on the Science of Social Media, we're examining the fascinating field of neuroscience and how it can positively influence our marketing productivity. Think of today's show as little tricks for your brain to work smarter, not harder.


6 Simple Ways to Use Neuroscience to Increase Marketing Productivity

#artificialintelligence

Neuroscience is a multidisciplinary science that is concerned with the study of the structure and function of the nervous system. When applied to our professional lives, neuroscience can help us to unlock our greatest potential. Increasing your meaningful productivity can have a huge impact on your day-to-day work and can greatly influence your professional success over a long period of time. This week on the Science of Social Media, we're examining the fascinating field of neuroscience and how it can positively influence our marketing productivity. Think of today's show as little tricks for your brain to work smarter, not harder.


r/MachineLearning - [D] AutoML/Neural Architecture Search has a giant CO2 footprint

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Energy does mean a thing. You are never creating energy, you are only transforming it. Meaning you are still taking energy from somewhere. Having enough energy for everyone to light their house is actually a rising problem since with less atom energy it gets harder to manage and distribute. While it gets hard to distribute that energy we are wasting tons of energy on ML.