If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
It's been a while since I last posted a new entry on the TorchVision memoirs series. Thought, I've previously shared news on the official PyTorch blog and on Twitter, I thought it would be a good idea to talk more about what happened on the last release of TorchVision (v0.12), what's coming out on the next one (v0.13) My target is to go beyond providing an overview of new features and rather provide insights on where we want to take the project in the following months. TorchVision v0.12 was a sizable release with dual focus: a) update our deprecation and model contribution policies to improve transparency and attract more community contributors and b) double down on our modernization efforts by adding popular new model architectures, datasets and ML techniques. Key for a successful open-source project is maintaining a healthy, active community that contributes to it and drives it forwards.
One of the easiest, and yet also the most effective, ways of analyzing how people feel is looking at their facial expressions. Most of the time, our face best describes how we feel in a particular moment. This means that emotion recognition is a simple multiclass classification problem. We need to analyze a person's face and put it in a particular class, where each class represents a particular emotion. In Python, we can use the DeepFace and FER libraries to detect emotions in images.
I had seen the Edge Impulse development platform for machine learning on edge devices being used by several boards, but I hadn't had an opportunity to try it out so far. So when Seeed Studio asked me whether I'd be interested to test the nRF52840-powered XIAO BLE Sense board, I thought it might be a good idea to review it with Edge Impulse as I had seen a motion/gesture recognition demo on the board. It was quite a challenge as it took me four months to complete the review from the time Seeed Studio first contacted me, mostly due to poor communications from DHL causing the first boards to go to customs' heaven, then wasting time with some of the worse instructions I had seen in a long time (now fixed), and other reviews getting in the way. But I finally managed to get it working (sort of), so let's have a look. Since the gesture recognition demo used an OLED display, I also asked for it and I received the XIAO BLE board (without sensor), the XIAO BLE Sense board, and the Grove OLED Display 0.66″.
Babak Hodjat is the CTO for AI at Cognizant where he leads a team of developers and researchers bringing advanced AI solutions to businesses. Babak is the former co-founder and CEO of Sentient, responsible for the core technology behind the world's largest distributed artificial intelligence system. Babak was also the founder of the world's first AI-driven hedge-fund, Sentient Investment Management. Babak is a serial entrepreneur, having started a number of Silicon Valley companies as main inventor and technologist. Prior to co-founding Sentient, Babak was senior director of engineering at Sybase iAnywhere, where he led mobile solutions engineering.
DALL·E 2 is a new AI system that can create realistic images and art from a description in natural language. DALL·E 2 can create original, realistic images and art from a text description. It can combine concepts, attributes, and styles. DALL·E 2 can make realistic edits to existing images from a natural language caption. It can add and remove elements while taking shadows, reflections, and textures into account.
By using this framework, anyone can build neural networks with graphs. This also depicts operations as nodes. PyTorch is one of the most important frameworks in artificial intelligence. However, it is super adaptable in terms of integrations and languages. It was released by Facebook's AI research lab. This also acts as an open source library useful in deep learning, computer vision and natural language processing software. Another feature is its greater affinity with iOS as well as Android etc. It uses debugging tools like IPDB and PDB.
Explains Nikola Konstantinov of Switzerland's ETH Zürich, "Fairness in AI is about ensuring that AI models don't discriminate when they're making decisions, particularly with respect to protected attributes like race, gender, or country of origin." As artificial intelligence (AI) becomes more widely used to make decisions that affect our lives, making certain it is fair is a growing concern. Algorithms can incorporate bias from several sources, from the people involved in different stages of their development to modelling choices that introduce or amplify unfairness. A machine learning system used by Amazon to pre-screen job applicants was found to display bias against women, for example, while an AI system used to analyze brain scans failed to perform equally well across people of different races. "Fairness in AI is about ensuring that AI models don't discriminate when they're making decisions, particularly with respect to protected attributes like race, gender, or country of origin," says Nikola Konstantinov, a post-doctoral fellow at the ETH AI Center of ETH Zürich, in Switzerland. Researchers typically use mathematical tools to measure the fairness of machine learning systems based on a specific definition of fairness.
It was an important milestone for a company that has, at least in the popular imagination, struggled to catch up with SpaceX. So it's fitting how Boeing decided it would celebrate a successful mission. When the crew of the ISS opened the hatch to Starliner, they found a surprise inside the spacecraft. Floating next to Orbital Flight Test-2's seated test dummy was a plush toy representing Jebediah Kerman, one of four original "Kerbonauts" featured in Kerbal Space Program. Jeb, as he's better known by the KSP community, served as the flight's zero-g indicator. Russian cosmonaut Yuri Gagarin took a small doll with him on the first-ever human spaceflight, and ever since it has become a tradition for most space crews to carry plush toys with them to make it easy to see when they've entered a microgravity environment.
Visions of Beauty became a personal challenge with Ai and the tools used to create these images. As powerful as Ai can be, there are many challenges when working with Google Colab notebooks. Firstly, there are the actual options within the notebook itself, all of which work in conjunction with the prompt to provide 'balance' to the final image... the vision that the artist wanted to capture. Along with the notebook settings and the actual prompt used to generate the image, there are modifiers which help the artist to convey emotion for his vision. Thousands of words, phrases, artists and more make the process fun, but very tiresome. Faces have proven to be very difficult with Ai. This was my challenge. Find a way to make Ai’s vision of beauty equal that of the creator.