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Exponential Progress, book review: A patchy overview of today's emerging technologies

ZDNet

The spacesuited figure on the cover makes it look like science fiction, the opening liability disclaimer would fit right into to an end-user licence agreement, the index is sandwiched between a 40-page bibliography and a handy list of abbreviations, from CAPTCHA to YOLO, that you probably know but might like an reminder of, and the whole book is covered by a Creative Commons licence. So how does this unusual approach to publishing stand up? The introduction to Exponential Progress purports to be written at the back end of the 21st century, reframing the usual'outhouse to zero-gravity toilet in 70 years' reference to the speed of progress as a 300-year jump from no electricity to'outer-terrestrial colonies' (along with hints about a civilisation of AIs). By promising to explain to fictional readers some eight decades in the future how we got there, author Farabi Shayor gets licence to cover the state of the art across a range of current and bleeding-edge technologies -- virtual reality, electric and self-driving cars, AI (both software and'brain-like' chips), the singularity, brain-computer interfaces, CRISPR and synthetic biology -- for a general audience. Although the book promises to explore the dangers of emerging technology and whether the pace of innovation is beyond human control, the writing is often unstintingly optimistic.


Report: State of Artificial Intelligence in India - 2020

#artificialintelligence

Artificial Intelligence or AI is a field of Data Science that trains computers to learn from experience, adjust to inputs, and perform tasks of certain cognitive levels. Over the last few years, AI has emerged as a significant data science function and, by utilizing advanced algorithms and computing power, AI is transforming the functional, operational, and strategic landscape of various business domains. AI algorithms are designed to make decisions, often using real-time data. Using sensors, digital data, and even remote inputs, AI algorithms combine information from a variety of different sources, analyze the data instantly, and act on the insights derived from the data. Most AI technologies – from advanced recommendation engines to self-driving cars – rely on diverse deep learning models. By utilizing these complex models, AI professionals are able to train computers to accomplish specific tasks by recognizing patterns in the data. Analytics India Magazine (AIM), in association with Jigsaw Academy, has developed this study on the Artificial Intelligence market to understand the developments of the AI market in India, covering the market in terms of Industry and Company Type. Moreover, the study delves into the market size of the different categories of AI and Analytics startups / boutique firms. As a part of the broad Data Science domain, the Artificial Intelligence technology function has so far been classified as an emerging technology segment. Moreover, the AI market in India has, till now, been dominated by the MNC Technology and the GIC or Captive firms. Domestic firms, Indian startups, and even International Technology startups across various sectors have, so far, not made a significant investment, in terms of operations and scale, in the Indian AI market. Additionally, IT services and Boutique AI & Analytics firms had not, till a couple of years ago, developed full-fledged AI offerings in India for their clients.


Opening the Software Engineering Toolbox for the Assessment of Trustworthy AI

arXiv.org Artificial Intelligence

Trustworthiness is a central requirement for the acceptance and success of human-centered artificial intelligence (AI). To deem an AI system as trustworthy, it is crucial to assess its behaviour and characteristics against a gold standard of Trustworthy AI, consisting of guidelines, requirements, or only expectations. While AI systems are highly complex, their implementations are still based on software. The software engineering community has a long-established toolbox for the assessment of software systems, especially in the context of software testing. In this paper, we argue for the application of software engineering and testing practices for the assessment of trustworthy AI. We make the connection between the seven key requirements as defined by the European Commission's AI high-level expert group and established procedures from software engineering and raise questions for future work.


Alphabet's Next Billion-Dollar Business: 10 Industries To Watch - CB Insights Research

#artificialintelligence

Alphabet is using its dominance in the search and advertising spaces -- and its massive size -- to find its next billion-dollar business. From healthcare to smart cities to banking, here are 10 industries the tech giant is targeting. With growing threats from its big tech peers Microsoft, Apple, and Amazon, Alphabet's drive to disrupt has become more urgent than ever before. The conglomerate is leveraging the power of its first moats -- search and advertising -- and its massive scale to find its next billion-dollar businesses. To protect its current profits and grow more broadly, Alphabet is edging its way into industries adjacent to the ones where it has already found success and entering new spaces entirely to find opportunities for disruption. Evidence of Alphabet's efforts is showing up in several major industries. For example, the company is using artificial intelligence to understand the causes of diseases like diabetes and cancer and how to treat them. Those learnings feed into community health projects that serve the public, and also help Alphabet's effort to build smart cities. Elsewhere, Alphabet is using its scale to build a better virtual assistant and own the consumer electronics software layer. It's also leveraging that scale to build a new kind of Google Pay-operated checking account. In this report, we examine how Alphabet and its subsidiaries are currently working to disrupt 10 major industries -- from electronics to healthcare to transportation to banking -- and what else might be on the horizon. Within the world of consumer electronics, Alphabet has already found dominance with one product: Android. Mobile operating system market share globally is controlled by the Linux-based OS that Google acquired in 2005 to fend off Microsoft and Windows Mobile. Today, however, Alphabet's consumer electronics strategy is being driven by its work in artificial intelligence. Google is building some of its own hardware under the Made by Google line -- including the Pixel smartphone, the Chromebook, and the Google Home -- but the company is doing more important work on hardware-agnostic software products like Google Assistant (which is even available on iOS).


Ten Ways the Precautionary Principle Undermines Progress in Artificial Intelligence

#artificialintelligence

Artificial intelligence (AI) has the potential to deliver significant social and economic benefits, including reducing accidental deaths and injuries, making new scientific discoveries, and increasing productivity.[1] However, an increasing number of activists, scholars, and pundits see AI as inherently risky, creating substantial negative impacts such as eliminating jobs, eroding personal liberties, and reducing human intelligence.[2] Some even see AI as dehumanizing, dystopian, and a threat to humanity.[3] As such, the world is dividing into two camps regarding AI: those who support the technology and those who oppose it. Unfortunately, the latter camp is increasingly dominating AI discussions, not just in the United States, but in many nations around the world. There should be no doubt that nations that tilt toward fear rather than optimism are more likely to put in place policies and practices that limit AI development and adoption, which will hurt their economic growth, social ...


32 artificial intelligence companies building a smarter tomorrow

#artificialintelligence

From Google and Amazon to Apple and Microsoft, every major tech company is dedicating resources to breakthroughs in artificial intelligence. Personal assistants like Siri and Alexa have made AI a part of our daily lives. Meanwhile, revolutionary breakthroughs like self-driving cars may not be the norm, but are certainly within reach. As the big guys scramble to infuse their products with artificial intelligence, other companies are hard at work developing their own intelligent technology and services. Here are 32 artificial intelligence companies and AI startups you may not know today, but you will tomorrow.


The 2018 Survey: AI and the Future of Humans

#artificialintelligence

"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.


30 tech innovators to watch in Europe 2019 Sifted

#artificialintelligence

What if there was no such thing as "real"? What if food could be made from thin air? What if electronics could last forever? These are some of the questions being tackled by Europe's top tech innovators identified by our team here at Sifted, in association with the co-working space Second Home and their Breakthrough event this month. This is not your ordinary innovator list. You may not have heard of these startups.


AI 50: America's Most Promising Artificial Intelligence Companies

#artificialintelligence

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and gets trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") are a core part of their business model and future success. Find all the details on our methodology here.


AI 50: America's Most Promising Artificial Intelligence Companies

#artificialintelligence

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and gets trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") are a core part of their business model and future success. Find all the details on our methodology here.