For years, the "millennial generation" has been the subject of derision from a wide range of different angles. They have been called things like "lazy," "entitled" and "delusional," to name a few. They were looked at as kids who were spoiled from birth and who expected to start at the top.
Software giant Microsoft has partnered with the Nevada Institute for Autonomous Systems ( NIAS) and the Nevada Governor's Office of Economic Development (GOED) to test Microsoft's Artificial Intelligence (AI) technology in a Microsoft sailplane. The 16 ½ -foot, 12 ½- pound sailplane used AI to stay in the air without a motor.
At its core, Amazon's goal is to remove as much friction as possible from a customer finding what they want, ordering it, and having it land on their doorstep. Its ambitions started with books, but have since extended to just about every other category, including clothes.
Spinal Tap had it right. As bassist Derek Albion Smalls and guitarist David St. Hubbins concluded in that send-up of the rockumentary, "There's a thin line between clever and stupid." We find that is true in data analytics more often these days. Yes, the difference between a clever algorithm and a stupid one can be very thin.
After school, he was awarded a place at King's College, Cambridge to read physics and chemistry but dropped out after a month. "I was 18 it was the first time I had lived apart from home. It was awfully hard work, there weren't any girls and I got depressed," he says.
Content management is about to undergo a foundational shift as artificial intelligence and machine learning bring long-sought order to enterprise content. As the volume of content has increased, the ability to manage it all seems to have alluded us. Ironic, since Content Management Systems were supposed to solve the enterprise content organization problem.
A hub for technological innovation and inspiration, Hot Chips delivered tutorials, presentations, and more. "Hot Chips 29: A Symposium on High-Performance Chips" was held August 20-22 at the Flint Center in Cupertino, California. The symposium, which has been around since 1989, is an industry-leading conference held annually to explore the world of high-performance microprocessors and related integrated circuits.
Fundamental and quantitative investing used to be the hedge-fund versions of oil and water: They didn't mix. Those in the fundamental camp do analysis the old-fashioned way, evaluating investments based on research and instinct, with humans calling the shots. Quantitative money managers turn to sophisticated computer algorithms that search mountains of data for hidden signals and then make rapid-fire investment decisions.
Though soccer players have assigned roles, it is routine for players to swap positions throughout the course of a game, or even during a single play. Players and fans recognize when this occurs and now, thanks to work led by engineers at Caltech, so can a computer.
Society is in a new age of digital customer service where on-demand help is expected 24/7, 365 days a year. Brands are recognising that customer service is an integral part of the customer journey, and they're upping their game to better understand the consumer's needs.
We've never met but I feel confident telling you this: It's going to be okay, I promise. Put the coffee down, and the e singularity is never going to happen, and the only winter people should be concerned about is the larger and harsher ones brought on by climate change, not an AI one.
A team of researchers from Oak Ridge National Lab oratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis.
Back in November, Google showcased a few of its funky machine learning experiments, and among them was Quick, Draw! (their bang, not mine) - a game where you sketch something and an image recognition system guesses what it is.
Early in August, NYU professor Siddharth Garg checked for traffic, and then put a yellow Post-it onto a stop sign outside the Brooklyn building in which he works. When he and two colleagues showed a photo of the scene to their road-sign detector software, it was 95 percent sure the stop sign in fact displayed a speed limit.
It's no secret that machine learning-based algorithms can be problematic and even inject or boost bias in decision-making processes. Software used by courts for sentencing decisions has been shown to make harsher recommendations for defendants of color. Alexandra Meliou and Yuriy Brun, both assistant professors at the University of Massachusetts at Amherst, have found a new technique to automatically test software for discrimination.
In this presentation, our friends Andy Steinbach, Head of AI in Financial Services at NVIDIA, and Patrick Hall, Senior Director of Product at H2O.ai discuss Machine Learning Interpretability with Driverless AI. Interpretability is a hugely popular topic in machine learning. Wherever possible, interpretability approaches are deconstructed into more basic components suitable for human storytelling: complexity, scope, understanding, and trust.
Quite possibly, doctors have a tough job to do monitoring several patients at one time, and sometimes standards can slip when they're given too heavy a workload. However, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have set put to change that by integrating machine learning techniques into patient care and to help doctors make better decisions.
Answer: No, it's apparently just an algorithm that is incapable of becoming hostile.
William White, InvestorPlace Writer Ford Motor Company (NYSE:) is planning to use machine learning to help it approve more loans. Ford Motor Credit Company, the financial business for the company, has completed a study with ZestFinance concerning the machine learning method of lending.
After Apple decided to allow its researchers to publicly share their findings, its first academic paper was published at the end of last year. Now, that research has just won a "Best Paper Award" at a prestigious machine learning and computer vision conference.
Artificial intelligence as a technology is rapidly growing, but much is still being learned about how AI and autonomous systems make decisions based on the information they collect and process.
The Interactive Advertising Bureau has established a working group of industry executives to tackle three areas that will shape the use of artificial intelligence and machine learning in the digital marketing space: recruiting talent, developing new approaches to creativity, and establishing insights. The IAB AI/Machine Learning for Marketing Purposes Working Group is headed by Co-Chairs Patrick ...
Kavya Kopparapu might be considered something of a "whiz kid." After all, she had yet to enter her senior year of high school when she started Eyeagnosis, a smartphone app and 3D-printed lens that allows patients to be screened for diabetic retinopathy with a quick photo, avoiding the time and expense of a typical diagnostic procedure.
Will artificial intelligence diminish the importance of human relationships?
Can computers be creative? That's a question bordering on the philosophical, but artificial intelligence (AI) can certainly make music and artwork that people find pleasing. Last year, Google launched Magenta, a research project aimed at pushing the limits of what AI can do in the arts.
Every year, tens of millions of Americans toss and turn with chronic sleep disorders. But diagnosis isn't easy: It usually means sleeping in a lab entangled in gadgets that track breathing, heart rate, movement, and brain activity, followed by expert analysis of the data.
Google is one of the pioneers of artificial intelligence (AI). In this article we look at the amazing ways Google is using the most cutting edge AI - deep learning - in many of its operations and how this is boosting their customer offerings and business performance.
Facebook is making steps to ensure that everyone gets their facts right before forming their own opinion on a topic trending on the popular social media platform. Recently, the company tweaked its Related Articles feature and introduced an updated machine ... Read More
For everyone frustrated by how long it takes to train deep learning models, IBM has some good news: It has unveiled a way to automatically split deep-learning training jobs across multiple physical servers -- not just individual GPUs, but whole systems with their own separate sets of GPUs.
In May last year, a stunning report claimed that a computer program used by a US court for risk assessment was biased against black prisoners. The program, Correctional Offender Management Profiling for Alternative Sanctions (Compas), was much more prone to mistakenly label black defendants as likely to reoffend - wrongly flagging them at almost twice the rate as white people (45% to 24%), according to the investigative journalism organisation ProPublica.
Add to favorites In 2014, UK insurers uncovered 130,000 fraudulent claims worth £1.32 billion across all insurance products. This danger shows no sign of slowing either, with professional and opportunistic insurance fraud numbers still on the rise. So, how can insurers effectively analyse data help to combat insurance fraud?
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In my series, I've looked at the different ways in which data can be deployed to help people make decisions. Over time, more of the decision-making process has shifted from people manually collating data from different sources in their heads to using data sets that can be automatically joined together.
Memes may be a fun pastime for a lot of us, but sometimes it's so hard to find the exact one you're looking for. Maybe you're looking for an old meme you just can't find, or there's a new one that's been doing the rounds you're looking for.
The same machine learning technology Google uses to anticipate the next word in a search query is in tests to advance predictive modeling in health care, and the tech giant is teaming up with three universities this year to research its ability to do so.
In the accounting, audit, and compliance professions, Artificial Intelligence(AI) is already beginning to automate labor-intensive tasks, such as data entry or combing through manual documents. For example, accounting and audit professionals may deploy AI to extract information from invoices or purchase orders to enter into accounting and auditing systems, freeing up hours in the day to perform more robust analytics on the outputs of the system.
As fields of research, machine learning and artificial intelligence both date back to the 50s. More than half a century later, the disciplines have graduated from the theoretical to practical, real world applications. We'll have some of the top minds in both categories to discuss the latest advances and future of AI and ML on stage and Disrupt San Francisco in just over a month.
Major tech companies have actively reoriented themselves around AI and machine learning: Google is now "AI-first," Uber has ML running through its veins and internal AI research labs keep popping up. They're pouring resources and attention into convincing the world that the machine intelligence revolution is arriving now.
The overall trend for retail sales volume is up, despite considerable disruption to the channels consumers use to make purchases.
It is the summer holidays and the schools are out. If you have children you have been watching the weather forecast, with increasing dread, hoping that tomorrow will bring brighter weather.
The rivalry between banks and FinTechs has, at times, been tense if not downright combative. Enter APIs to help the two sides coexist more peacefully. API solutions are doing more than helping two different types of financial institutions find ways to collaborate.
If we were to ask you to gather a group of three people to carry large stones block by block to build an Egyptian Pyramid, would you think we're crazy? What if we gave you an infinite amount of time? And if you and the rest of your group are physically very strong?
On August 31, 2012, four Amazon engineers filed the fundamental patent for what ultimately became Alexa, an artificial intelligence system designed to engage with one of the world's biggest and most tangled data sets: human speech. The engineers needed just 11 words and a simple diagram to describe how it would work.
According to Gartner, the chance of a BI initiative not meeting enterprise objectives is a staggering 70 percent. That is because the answers to current business needs can not be answered by BI alone. Even if you didn't like calculus in High School, Maya Gal, founder of Okapi has a powerful equation which explains what organizations need to do in order to achieve operational excellence.
Leave it to the experts in machine learning to figure out that "machine learning" has lost its oomph. When it comes to terms in job postings which help fill those jobs more quickly, "artificial intelligence" and "AI" are also waning, according to Textio, the Seattle startup that analyzes the words that work.
Machines are getting better at thinking for themselves. Microsoft's DeepCoder, for example, has learnt to write its own code. And Google has built Federated Learning - a tool that automatically personalizes apps directly on users' devices. For marketers, this evolution in machine learning has enormous potential: almost all ( 98%) think it will benefit their marketing efforts.
To learn how humans and AI systems can best live together, we may need to kill a whole lot of Zerg. DeepMind, the AI-focused unit of Alphabet, and the games company Blizzard Entertainment are releasing a set of tools that will let will programmers unleash all sorts of AI algorithms inside the space-themed game StarCraft.
CHICAGO -- As hospitals and health systems leverage information technology, healthcare executives must advocate for caregivers to improve provider satisfaction, be prepared for a telehealth explosion, embrace machine learning and artificial intelligence, incorporate the Internet of Things, and prepare for more cyber-attacks, said Thomas Zenty, CEO of University Hospitals of Cleveland.
On July 18th Yandex announced the launch of a state-of-the-art open-sourced machine learning algorithm called CatBoost that can be easily integrated with deep learning frameworks like Google's TensorFlow and Apple's Core ML. Unlike deep learning tools that support only certain types of data, CatBoost works with more diverse types of data to help solve a wide range of problems that businesses face today with best-in-class accuracy.
