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) …
We recently got the chance to help one of our start-up clients from the Oil and Gas research domain. They have to deal with heavy workloads on AWS for their application. This was achieved by training and deploying a lot of machine learning models using AWS SageMaker and AWS EC2. AWS SageMaker is a tool that helps the data scientists and developers to quickly build and deploy applications within a hosted environment. Also, AWS EC2 or elastic Compute Cloud is the tool for providing scalable computing capacity across different virtual servers.
But it can step in when companies misrepresent the capabilities of a product they are selling, which means firms that claim their facial recognition systems, predictive policing algorithms or healthcare tools are not biased may now be in the line of fire. "Where they do have power, they have enormous power," says Calo. In the blog post, the FTC warns vendors that claims about AI must be "truthful, non-deceptive, and backed up by evidence." The result may be deception, discrimination--and an FTC law enforcement action." The FTC action has bipartisan support in the Senate, where commissioners were asked yesterday what more they could be doing and what they needed to do it. But it can step in when companies misrepresent the capabilities of a product they are selling, which means firms that claim their facial recognition systems, predictive policing algorithms or healthcare tools are not biased may now be in the line of fire. "Where they do have power, they have enormous power," says Calo. In the blog post, the FTC warns vendors that claims about AI must be "truthful, non-deceptive, and backed up by evidence." The result may be deception, discrimination--and an FTC law enforcement action."
Klara, the narrator of the new novel by Kazuo Ishiguro, isn't human, but understanding humans is her mission. In Klara and the Sun, the reader follows her in that mission, in a world that seems like our own in a none too distant future. Ishiguro, who was born in Japan but has lived most of his life in England, has written seven previous novels, including the Booker Prize-winning The Remains of the Day, as well as short fiction, song lyrics and screenplays. Klara and the Sun is his first novel since he received the Nobel Prize for literature in 2017. It underscores how well he deserved that prize, in its beautiful craft and prose and in its tender but unflinching sense of the human heart.
Panasonic has gone all-in on a past investment into Blue Yonder to fully acquire the company in a deal worth $7.1 billion. Under the terms of the purchase, made public on Friday, Panasonic will acquire 80% of remaining shares from Blue Yonder for $5.6 billion. The acquisition terms also require the repayment of outstanding debt, bringing the total value of the purchase to $7.1 billion. Panasonic purchased a 20% stake in Blue Yonder last year for roughly $790 million, deepening an existing partnership between the companies that was forged in January 2019 -- followed by the creation of a joint venture (JV) in April of the same year. Founded in 1985 and led by CEO Girish Rishi, Blue Yonder is a supply chain solutions provider and the creator of the Luminate platform.
Once upon a time, there was the AAAI 2005 Fall Symposium on Machine Ethics. It is the one event perhaps that I wish I could have attended, otherwise I do not entertain desires of being older. Much of the work in machine ethics can be traced back to the discussions at that seminar, but they also seemed to have spurred many questions that we still find interesting. When the AAAI 2021 Spring Symposium on Implementing AI Ethics was announced, it was not difficult to clear the schedule for "a deeper discussion on how intelligence, agency, and ethics may intermingle in organizations and in software implementations". The 2021 symposium has not per definition been the spiritual descendant of the 2005 seminar, but by composition of participants and discussion structure, I expect great ideas will be developed after this one as well.
If you list the biggest and fastest-growing technologies over the past decade, artificial intelligence (AI) will inarguably top the charts. The global AI market was valued at 39.9 billion in 2019 and is projected to grow at a CAGR of 42.2% during 2020-2027, according to Grand View Research. AI has found applications in every industry, and the fitness sector is no different. Smart fitness wearables, AI-powered fitness apps, and AI and Machine Learning (ML) for gym management are common use cases of AI in fitness. But not many people thought that there would come a time when AI will be on the verge of replacing personal trainers and fitness coaches.
Nearly two years since its massive 1.2 trillion transistor Wafer Scale Engine chip debuted at Hot Chips, Cerebras Systems is announcing its second-generation technology (WSE-2), which its says packs twice the performance into the same 8″x8″ silicon footprint. "We're going bigger, faster and better in a more power efficient footprint," Cerebras Founder and CTO Andrew Feldman told HPCwire ahead of today's launch. With 2.6 trillion transistors and 850,000 cores, the WSE-2 more than doubles the elements on the first-gen chip (1.2 trillion transistors, 400,000 cores). The new chip, made by TSMC on its 7nm node, delivers 40 GB of on-chip SRAM memory, 20 petabytes of memory bandwidth and 220 petabits of aggregate fabric bandwidth. Gen over gen, the WSE-2 provides about 2.3X on all major performance metrics, said Feldman.
Organizations implementing AI applications have several considerations to ponder in choosing the proper infrastructure. But one critical consideration is making a distinction between the training portion of AI and inferencing. This is the view of Michael Lang, solutions architecture manager at NVIDIA, speaking on a panel discussion on implementing AI at the recent NexGen Connectivity Forum. The forum comprised both industry participants and solution providers. The training and learning piece of AI, said Lang, is very different and often requires a different infrastructure environment to the one used for inferencing with AI. "The training and learning piece is about HPC and data-intensive needs," said Lang. "That means big data centers and infrastructure and big capability."
A part of what we see in science fiction movies will soon become a reality, thanks to artificial intelligence. Every time you saw people talking to holograms in sci-fi movies and thought to yourself "that would be awesome to have", you just might be closer to that future. Smartphones will soon be able to create photorealistic 3D holograms with an AI model developed by a research team at MIT. This system determines the best way to generate holograms from a sequence of input images. This fascinating technology could have applications for VR and AR headsets.
Subex has launched HyperSense, an end-to-end Augmented Analytics platform that helps enterprises make faster, better decisions by leveraging Artificial Intelligence (AI) across the data value chain. Developed based on Subex's extensive data analytics experience, HyperSense contains all the Augmented Analytics capabilities enterprises need in one flexible and modular platform. HyperSense's unique no-code capabilities allow users without a knowledge of coding to easily aggregate data from disparate sources, turn data into insights by building, interpreting, and tuning AI models, and effortlessly share their findings across the organization. First defined by Gartner, Augmented Analytics uses enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation. It empowers experts as well as non-data scientists by automating many aspects of data science, including model development, management and deployment of AI models.