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) …
Yandex, the Russian Alphabet-like company with a self-driving car unit that debuted a fully driverless car in Las Vegas this year, has updated its autonomous driving program. The fourth iteration of the company's self-driving car was officially revealed on Tuesday as a modified Hyundai Sonata. Up until now, Yandex had used hybrid Toyota Priuses, with a fleet of 100 of the self-driving vehicles, including some offering taxi rides in a Russian city. In March five of the new Sonatas were sprinkled into the Moscow fleet. By the end of this year, 100 of the Sonatas will join the collection of electric rides in Russia and Yandex's soon-to-arrive self-driving program in Michigan.
A few years ago at its Build developer conference, Microsoft made its conversation as a service (CaaS) offerings the centerpiece of its announcements. This year, Microsoft made some solid advancements with its bot services, but didn't trumpet them nearly as loudly. Azure Bot Service is for customers who want to build enterprise-grade bots while maintaining control of their data. Microsoft Bot Framework is for users who want to build custom bots which can be used as integrated component. Microsoft's Virtual Assistant Solution Accelerator is now generally available.
The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, and figuring out where the data science team fits in and what algorithms to buy versus build. Dell Technologies is rolling out a series of designs and systems that aim to speed up artificial intelligence deployments by using VMware's acquired Bitfusion technology. Two Dell EMC Ready Solutions are based on VMware Validated Designs to combine Dell EMC hardware with VMware Cloud Foundation and AI management Bitfusion tools in VMware vSphere 7. Dell Technologies said that its Dell Dell Technologies is claiming to be among the first IT companies to equip systems to run AI workloads within VMware environments. Ravi Pendekanti, senior vice president of product management and marketing for Dell Technologies server unit, said the new systems are designed to run AI anywhere and take advantage of underutilized GPUs. "GPU instances are being underutilized and that is holding back AI," said Pendekanti.
One of the challenges to curbing the spread of COVID-19 is that asymptomatic individuals, or carriers, can spread the virus before they realize they are infected. In April, researchers from West Virginia University's (WVU) Rockefeller Neuroscience Institute (RNI) and WVU Medicine set out to predict symptoms before they appear using wearable rings by Oura and AI prediction models. Now, the researchers claim their digital platform can detect COVID-19 related symptoms up to three days early with over 90 percent accuracy. The approach is neuroscience-based, and it asks participants to track stress, anxiety, memory and other psychological and cognitive biometrics in the RNI app. Oura Ring collects physiological data, like body temperature, heart rate variability, resting heart rate, respiratory rate and sleep patterns.
The automation wave has overtaken IT departments everywhere making DevOps a critical piece of infrastructure technology. DevOps breeds efficiency through automating software delivery and allowing companies to push software to market faster while releasing a more reliable product. What is next for DevOps? We need to look no further than artificial intelligence and machine learning. Most organizations quickly realize the promise of AI and machine learning, but often fail to understand how they can properly harness them to improve their systems.
The artificial intelligence model showed great promise in predicting which patients treated in U.S. Veterans Affairs hospitals would experience a sudden decline in kidney function. But it also came with a crucial caveat: Women represented only about 6% of the patients whose data were used to train the algorithm, and it performed worse when tested on women. The shortcomings of that high-profile algorithm, built by the Google sister company DeepMind, highlight a problem that machine learning researchers working in medicine are increasingly worried about. And it's an issue that may be more pervasive -- and more insidious -- than experts previously realized, new research suggests. The study, led by researchers in Argentina and published Monday in the journal PNAS, found that when female patients were excluded from or significantly underrepresented in the training data used to develop a machine learning model, the algorithm performed worse in diagnosing them when tested across across a wide range of medical conditions affecting the chest area.
Times have changed and caught most of us unprepared. It is always a part of Bolt's culture to move quickly and adapt -- and the crisis situation that is unfolding due to a pandemic definitely requires significant adaptation. This is a look from inside Bolt's data team -- data analysts, data engineers, data scientists -- as we share our experience and advice for times of crisis with all the similar teams out there. Most of the resources are thrown into surviving and, for some, even on seizing new opportunities. Data teams definitely have a role to play in this.
Recent surveys, studies, forecasts and other quantitative assessments of AI highlight the number of manufacturing jobs eliminated by robots; why robots could replace financial analysts; the very small number of organizations not evaluating or using AI today; and the debate over the usefulness of Covid-19 contact-tracing. And as data quality and diversity increase from the wearables and other internet-of-things devices, a virtuous cycle of improvements will kick in. In this world a novel coronavirus could be tracked, traced, intercepted, and cut off before it got going"--Kai-Fu Lee
It would be illogical today to think that AI completely replaces human creativity. Having two such powerful "machines" and deleting one of them would be an absolute mistake. Instead, we should take advantage of 200% of the potential offered by both, an awesome combination impossible to replace. Let's talk about art, music, dance, writing, … "Being creative means being in love with life", being able to generate new ideas or concepts spontaneously. Does AI take place in these fields?