TLDR: Scroll down to Conclusions.
Elon Musk has recently unveiled his company’s first Neuralink device implanted in an experimental animal — a pig.
From the Merriam-Webster dictionary:
Avatar derives from a Sanskrit word meaning “descent,” and when it first appeared in English in the late 18th century, it referred to the descent of a deity to the earth — typically, the incarnation in earthly form of Vishnu or another Hindu deity. It later came to refer to any incarnation in human form, and then to any embodiment (such as that of a concept or philosophy), whether or not in the form of a person. In the age of technology, avatar has developed another sense — it can now be used for the image that a person chooses as his or her “embodiment” in an electronic medium.
San Francisco-based AI research laboratory OpenAI has added another member to its popular GPT (Generative Pre-trained Transformer) family. In a new paper, OpenAI researchers introduce GPT-f, an automated prover and proof assistant for the Metamath formalization language.
While artificial neural networks have made considerable advances in computer vision, natural language processing, robotics and so on, OpenAI believes they also have potential in the relatively underexplored area of reasoning tasks. The new research explores this potential by applying a transformer language model to automated theorem proving.
Automated theorem proving tends to require general and flexible reasoning to efficiently check the correctness of proofs. This makes it an appealing domain for checking the reasoning capabilities of language models and for the study of reasoning in general. The ability to verify proofs also helps researchers as it enables the automatic generation of new problems that can be used as training data.
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In the last video in this series we discussed the differences between deep learning and machine learning, how and when the field of deep learning was officially born, and it’s rise to mainstream popularity. The focus of this video then will be on artificial neural networks, more specifically – their structure.
Continue reading “How Neural Networks Work (From The Brain To Artificial Intelligence)” »
In 1998, an engineer in Sony’s computer science lab in Japan filmed a lost-looking robot moving trepidatiously around an enclosure. The robot was tasked with two objectives: avoid obstacles and find objects in the pen. It was able to do so…
The National Science Foundation has awarded a highly competitive $5 million grant to Vanderbilt University that greatly expands a School of Engineering-led project for creating novel AI technology and tools and platforms that train and support individuals with Autism Spectrum Disorder in the workplace.
The significant federal investment follows a successful $1 million, nine-month pilot grant to the same team that forged partnerships with employers and other stakeholders and produced viable prototypes through immersive, human-centric design. The multi-university team includes Yale University, Cornell University, Georgia Institute of Technology and Vanderbilt University Medical Center as academic partners.
Deep neural networks (DNNs) are essentially formed by having multiple connected perceptrons, where a perceptron is a single neuron. Think of an artificial neural network (ANN) as a system which contains a set of inputs that are fed along weighted paths. These inputs are then processed, and an output is…
Circa 2018 aerodrums.
LAS VEGAS (PRWEB) January 09, 2018.
Aerodrums today celebrates the live playing of an experimental variant of its air drumming instrument as part of a ground breaking musical performance introducing Intel’s keynote at CES 2018.
Continue reading “Aerodrums Air Drumming Instrument Played at Opening Keynote of CES 2018” »
Circa 2018
Tesla is known for its electric vehicles — but now it’s hoping to add trucks to its roster of roadsters. Here’s everything we know so far.
When the COVID-19 shutdown began in March throughout the United States, my team at Adobe had to face a stark reality: Business as usual was no longer an option. Suddenly, over just a single weekend, we had to shift our global workforce of over 22,000 people to working remotely. Not surprisingly, our existing processes and workflows weren’t equipped for this abrupt change. Customers, employees, and partners — many also working at home — couldn’t wait days to receive answers to urgent questions.
We realized pretty quickly that the only way to meet their needs was to completely rethink our support infrastructure.
Our first step was to launch an organization-wide open Slack channel that would tie together the IT organization and the entire Adobe employee community. Our 24×7 global IT help desk would front the support on that channel, while the rest of IT was made available for rapid event escalation.
