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) …
At some point, the machine demonstrates that it gets the difference between two dots and ten dots--regardless of how those dots appear on the screen. This ability to abstract quantities and distinguish between the resulting numbers may not seem like a big deal because it's so easy for humans. But new research shows that machines now have this ability to conceptualize numbers--something we might think of as "artificial numerosity." Numerosity is the ability to recognize specific quantities. It's the ability to tune our perception of objects so that we sense how many of them there are.
D.A., A.P.K., S.B. and B.C. developed the network architecture and data/modeling infrastructure, training and testing setup. D.A. and A.P.K. created the figures, wrote the methods and performed additional analysis requested in the review process. D.P.N. and J.J.R. provided clinical expertise and guidance on the study design. G.C and S.S. advised on the modeling techniques. M.E., S.S., J.J.R., B.C., W.Y. and D.A. created the datasets, interpreted the data and defined the clinical labels.
"It began three and a half billion years ago in a pool of muck, when a molecule made a copy of itself and so became the ultimate ancestor of all earthly life. It began four million years ago, when brain volumes began climbing rapidly in the hominid line. In less than thirty years, it will end." Jaan Tallinn stumbled across these words in 2007, in an online essay called "Staring into the Singularity." The "it" is human civilization.
Facebook is trying to develop artificial intelligence models that will allow robots–including walking hexapods, articulated arms, and robotic hands fitted with tactile sensors–to learn by themselves, and to keep getting smarter as they encounter more and more tasks and situations. In the case of the spider-like hexapod ("Daisy") I saw walking around a patio at Facebook last week, the researchers give a goal to the robot and task the model with figuring out by trial and error how to get there. The goal can be as simple as just moving forward. In order to walk, the spider has to know a lot about its balance, location, and orientation in space. It gathers this information through the sensors on its legs.
Deep Learning is really starting to establish itself as a major new tool in visual effects. Currently the tools are still in their infancy but they are changing the way visual effects can be approached. Instead of a pipeline consisting of modelling, texturing, lighting and rendering, these new approaches are hallucinating or plausibly creating imagery that is based on training data sets. Machine Learning, the superset of Deep Learning and similar approaches have had great success in image classification, image recognition and image synthesis. At fxguide we covered Synthesia in the UK, a company born out of research first published as Face2Face.
You know about Cortana, Siri and Google Assistant, right? Have you ever imagined that you can make your own virtual personal assistant and customize it as you want? Today, we'll be doing it here. We'll be building a personal assistant from scratch in python. Oh, Before getting into it, let me tell you that by no means it's an AI but just a powerful example of what AI can do, and how versatile and amazing python is.
Israeli radiology startup Aidoc has received FDA clearance for its AI-based product meant to help identify potential cases of pulmonary embolism in chest CT scans. Pulmonary embolism (PE) – which occurs when a blood clot gets lodged in the lung – is considered a silent killer that causes up to 200,000 deaths a year in the United States. The condition often strikes with little to no warning and diagnosis of a case can be extremely time-sensitive. Aidoc's technology doesn't require dedicated hardware and runs continuously on hospital systems, automatically ingesting radiological images. The 70-person company focuses on workflow optimization in radiology to help triage high risk patients for additional and faster review.
A key challenge in health informatics is "interoperability": the ability to exchange information seamlessly across disparate information systems. One must understand the meaning of the information. Imagine someone gave you a spreadsheet about a large set of patients, including the maximal diameter of the infrarenal aorta recorded in a column labeled "Aorta." Most of the values are integers that range from 23 to 55, so you assume (correctly) that these represent the diameter of the aorta in millimeters. But one patient has a value of 0, and another has 99.
Over the last few years, India has taken significant steps towards adoption of emerging technologies like artificial intelligence (AI) and machine learning(ML), with technology solutions providers, tech leaders, startups and government agencies playing a significant role in shaping the evolution of the technology in the country. According to a recent study, which observed the country-wide AI readiness in the Asia Pacific, India was ranked third in readiness, with its overall readiness score being 50.2 out of100, while Singapore was ranked the first with 63 points and Hong Kong was at the second with 56.5 points. As straightforward as it might sound, AI readiness simply does not refer a country's preparedness in embracing AI, rather, a number of key factors like the ability of its consumers, businesses and government to adopt, deploy and support AI technologies are taken into consideration to better understand the readiness capability of a country in adopting AI. In other words, AI readiness is not a linear process instead, multiple factors shape the outcome. "AI adoption is fragmented and uneven across the region. In some cases, governments' efforts and commitment have yet to be reflected in businesses' or consumers' adoption and usage of AI. In others, business and consumers are taking the lead, showing governments the way forward in terms of change and innovation," Eric Loeb EVP, Global Government Affairs points out in the study.
Hailo, an AI startup based in Israel, has released its initial chip that the company claims is "the world's top performing deep learning processor," with the Hailo-8 chip claimed to deliver 26 tera-operations pers second (TOPS), while consuming only a few watts of power. If true, that would certainly put it near or at the top of its class in performance for edge applications in areas like self-driving cars, drones, smart appliances, and virtual/augmented reality devices. The challenge in these edgey environments has always been to get AI processors with the requisite performance for these applications but consuming only the small amounts of power available in these settings. In fact, Hailo is positioning its new offering as chip that "enables edge devices to run sophisticated deep learning applications that could previously run only on the cloud." However, doesn't mean Hailo-8 is as powerful as a top-of-the-line inference GPU for the datacenter.