A Happy Meal and AI might not be the most obvious pairing but 2019 has seen McDonald's hit the headlines for its fast-paced investments in tech. In March, it acquired online personalisation startup Dynamic Yield for more than £232.8m This sparked a series of acquisitions, paving the way for what seems like the beginning of a journey for the iconic fast food chain to become the Amazon of food. A month later, it bought a 9.9% stake in mobile software company Plexure in a deal valued at about £3.8m, according to reports. The New Zealand-based company already helps with McDonald's mobile app but this surge of investment will see the chain have unprecedented access to Plexure's new tech for its app.

Testing specialists Applause have debuted an AI solution promising to help tackle algorithmic bias while providing the scale of data needed for robust training. Applause has built a vast global community of testers for its app testing solution which is trusted by brands including Google, Uber, PayPal, and more. The company is leveraging this relatively unique asset to help overcome some of the biggest hurdles facing AI development. AI News spoke with Kristin Simonini, VP of Product at Applause, about the company's new solution and what it means for the industry ahead of her keynote at AI Expo North America later this month. "Our customers have been needing additional support from us in the area of data collection to support their AI developments, train their system, and then test the functionality," explains Simonini.

Social media platforms have become overrun with fake news, creating the need for smart AI-based filters to separate fact from fiction. Fake news has become a nearly inescapable part of the social media experience. Social media has become a massive part of how we exchange information. There are now 3.48 billion active social media users in the world, with individuals and organizations recognizing the importance of these platforms as the primary means of interacting with the public. From local celebrities to world leaders like US President Donald Trump, everyone is using social media to deliver stories and messages, and the medium has proven to be an incredibly effective tool for influencing opinions.

Bank has hired technology leader Dr. Tanushree Luke to lead Artificial Intelligence (AI) efforts at the company. In this role, she will drive the continued development of the AI practice within the U.S. Bank Innovation group and AI strategies across the enterprise. Dr. Luke's career has spanned multiple industries and sectors. She joins U.S. Bank from Capital One, where she served as the Head of Predictive AI and Machine Learning for Capital One's Conversational AI Platform/Eno. Prior to that, Dr. Luke was the Chief Data Scientist at BitVoyant and was also previously a Technical Lead for the Department of Defense/DARPA Network Defense Program.

Technology, artificial intelligence and automation are supposed to solve our biggest problems, not create new ones or exacerbate existing issues. Unbeknownst to many, big tech is actually putting a huge burden on the environment. In a study assessing the energy consumption required to train several common large AI models, Researchers at the University of Massachusetts Amherst said artificial intelligence emissions can be over 626,000 pounds of carbon dioxide, which is about 5 times as much the lifetime emissions of an average car. According to research firm IDC, spending on AI systems is exploding, with the figure expected to hit nearly $98 billion in 2023, more than 3.5 times the $37.5 billion being spent this year. The U.S. is expected to deliver more than half of that spending through the forecast, which will be led by the retail and banking industries, according to IDC.

When Amazon demonstrated the new Echo Studio at a company event in September, I was blown away. This was some of the best audio I had ever heard from a little speaker, filling a room of hundreds of journalists and sounding like it was many speakers connected together. My initial thought was that rival Sonos, which specializes in great-sounding Wi-Fi speakers, was in trouble. After spending several hours with the $200 Studio, out Thursday, there will be no need to schedule a benefit for Sonos. The Studio does sounds great.

Medial EarlySign's CMO, Dr. Jeremy Orr, will be speaking at a session entitled "Analyte to Algorithm to Action to Impact" at G2 Intelligence's 37th Annual Lab Institute. Machine learning models are beginning to play a critical role in care transformation efforts, especially as they relate to risk adjustment, population health, and alternative payment models. Dr. Orr will review the development and validation of several powerful models to predict high burden disease at earlier, more treatable stages. He will further review the challenge of getting these predictors into clinical and laboratory workflow, how ML results are messaged to both patients and clinicians, and how clinical outcomes related to these predictors are measured. Dr. Orr will close with a look ahead to how ML models and approaches will improve care delivery for laboratorians and other clinicians, and how ML empowers the transition to value based care.

Artificial intelligence (AI) is a branch of computer science that attempts to emulate human problem-solving skills. Also called cognitive computing, AI includes concepts such as machine learning -- including deep learning and natural language processing -- which are especially relevant to health care. Mayo Clinic views AI as a set of techniques and technologies that serve to augment, rather than replace, human intelligence. AI excels in discerning patterns in complex data sets that may not be easily detected using human analysis. Patterns that are nuanced and highly multifactorial and those buried in an extremely large data set are often difficult for any individual human to navigate or detect.

The field of medicine faces a global shortage of radiologists, combined with increasing workloads and complex diagnoses, leading to delays, missed findings and huge overtime expenses in healthcare. A radiologist will upload a scan and mark a region of interest. Each result is a full volume, so radiologists can scroll through or change the contrast or brightness. Radiologists can even restrict results based on age, gender or pathological findings in the report via text search. How does Julia help make this possible?

The San Francisco software vendor's roots lie in the storage, backup and archive of massive amounts of unstructured data on commodity servers running a commercially supported version of OpenStack Swift. But SwiftStack has steadily expanded its reach over the last eight years, and its 7.0 update takes aim at the new scale-out storage and data management architecture the company claims is necessary for AI, machine learning and analytics workloads. SwiftStack said it worked with customers to design clusters that scale linearly to handle multiple petabytes of data and support throughput of more than 100 GB per second. That allows it to handle workloads such as autonomous vehicle applications that feed data into GPU-based servers. Marc Staimer, president of Dragon Slayer Consulting, said throughput of 100 GB per second is "really fast" for any type of storage and "incredible" for an object-based system.