One of the most common potential scenarios involving autonomous cars is using them as driverless taxis; both Uber and Lyft have made self-driving cars a big part of their future strategies. The possibility of hopping into a ride without a driver just got a little closer, at least in California -- as spotted by The Verge, California approved two new autonomous driving programs last week that let companies charge fares for autonomous rides. The two new programs are the "Drivered Autonomous Vehicle Deployment Program" and the "Driverless Autonomous Vehicle Deployment Program," both of which allow approved participants to offer "passenger service, shared rides, and accept monetary compensation for rides in autonomous vehicles." Naturally, interested companies need to get the necessary permits and show the California Public Utilities Commission (CPUC) that they're taking the proper safety measure. They'll need to get a AV Deployment Permit from California's DMV as well as one of two permits issued by CPUC.
I know for sure that human behavior could be predicted with data science and machine learning. Taking a look at human behavior from a sales data analysis perspective, we can get more valuable insights than from social surveys. In this article, I want to show how machine learning approaches can help with customer demand forecasting. Since I have experience in building forecasting models for retail field products, I'll use a retail business as an example. Moreover, considering uncertainties related to the COVID-19 pandemic, I'll also describe how to enhance forecasting accuracy.
On 1st January 2019, we (Fabin Rasheed and I) had introduced to the world, a side project we've been working on for months. An artificial poet-artist, who doesn't physically exist in this world but writes a poem, draws an abstract art based on the poem and finally color the art based on emotion. We called "her" Auria Kathi -- an anagram for "AI Haiku Art". Auria has an artificial face along with her artificial poetry and art. Everything about Auria was built using artificial neural networks.
State officials hope California's new 10 p.m. stay-at-home order will slow the spread of COVID-19, otherwise, another 10,000 San Diegans are projected to contract the virus in the next 10 days. That's according to a new county-by-county forecast from Facebook, which rolled out the prediction software last month. Facebook projects L.A. County will see the second-largest increase in cases in the country by November 30. San Diego County is projected to add the 15th most cases, reaching a total of 78,594 infections by Nov. 30. The two-week forecast was released before Governor Gavin Newsom announced enhanced restrictions.
When Deloitte's recent State of AI in the Enterprise study asked AI adopters about their organization's top adoption challenges, "managing AI-related risks" topped the list--tied with integration and data challenges, and on par with implementation concerns.1 And while worry is high, action to ameliorate risks is lagging: Fewer than one-third practice more than three AI risk management activities.2 And fewer than four in 10 adopters report that their organization is "fully prepared" for the range of AI risks that concern them. To investigate whether actively managing AI risks has any tangible benefit, we compared two groups of AI adopters that approach those risks differently: Risk Management Leaders (11%) undertake more than three AI risk management practices and align their AI risk management with their organization's broader risk management efforts, while Risk Management Dabblers (51%) undertake up to three AI risk management practices but are not aligning them with broader risk management efforts.3 The Leaders believe AI has greater strategic importance to their business: 40% see AI as "critically important" to their business today, versus only 18% of the Dabblers--and within two years, those numbers are expected to rise to 63% and 36%, respectively.
Artificial intelligence (AI) is swiftly fueling the development of a more dynamic world. AI, a subfield of computer science that is interconnected with other disciplines, promises greater efficiency and higher levels of automation and autonomy. Simply put, it is a dual-use technology at the heart of the fourth industrial revolution. Together with machine learning (ML) -- a subfield of AI that analyzes large volumes of data to find patterns via algorithms -- enterprises, organizations, and governments are able to perform impressive feats that ultimately drive innovation and better business. The use of both AI and ML in business is rampant.
He said the technology will be rolled out in the coming months across all Metro stations in the emirate. Dubai Police's smart glasses called Rokid T1, and the smart helmets that were used during the COVID-19 pandemic to scan commuters' temperatures, will have more advanced technology in the future like facial recognition to identify wanted people. "Usually, it takes at least five hours to identify a suspect, but with facial recognition technology, it takes less than a minute."
Sure, Spider-Man: Miles Morales and the Dark Souls remake are getting most of the PlayStation 5 love, but Sony's most significant next-generation launch game may be Astro's Playroom. It's a showpiece for the new DualSense controller's haptic capabilities, which includes finely tuned rumbling and adaptive triggers with adjustable tension. Best of all, you can start playing it on your PS5 right away; it's pre-installed on every system. Just like with Astro Bot Rescue Mission on the PlayStation VR, the diminutive robot is the ideal guide as Sony breaks new ground with hardware. As I mentioned in my PlayStation 5 review, simply booting up the game jolted me awake -- it vibrated in my hands as if it was the one holding me.
It sounds like the set-up for a violent revenge movie. Low-ranking yakuza Ichiban Kasuga takes the blame for an inter-clan assassination and does 18 years in prison to protect the organisation's patriarch. But, on his release, the gang disowns him and the boss, who he considers a father figure, shoots him and leaves him for dead. Surely, the stage is set for bloody retribution? Kasuga is not that kind of protagonist.
Ever since IBM unveiled Cloud Pak for Data as a cloud-native integrated set of analytics and AI platform, we've been wondering when IBM would take the next step and announce a full-blown managed cloud service. It's now starting to happen as IBM is rolling out IBM Cloud Pak for Data as a Service. Roll back the tape to last spring when we reviewed IBM Cloud Satellite; we noted that IBM's primary cloud message has been about multi-cloud, or at least cloud-agnostic. Propelled by Red Hat OpenShift, IBM carved out such a strategy for this managed Kubernetes environment where you could deploy open source software yourself on the hardware or public cloud of your choice or choose IBM to run a managed OpenShift service for you in the IBM Cloud. That is now getting repeated with Cloud Pak for Data.