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A PwC study in 2017 estimated the world would gain $15.7 trillion by 2030 if artificial intelligence (AI) was adopted across nations. The study said that AI would first lead to productivity enhancement, and a major portion of gains would accrue from consumer-side effects. China, it had said, could see its GDP rising by around a fourth as it was using AI more aggressively. Although the study did not estimate how much India would gain from using AI, new research by Icrier along with Nasscom and Google shows that even a marginal increase in artificial intelligence adoption may add 2.5% to GDP in the immediate term. Moreover, it highlights that if the government spends the Rs 7,000 crore it had envisaged for the national AI programme, GDP could get boosted by as much as $86 billion. The way Icrier sees it, as AI becomes what it calls a general purpose technologylike the internetits impact rises; essentially, then, the pace of Indias digitisation drive will determine how fast AI is adopted.

To understand how fast the adoption of AI can take place and its impact on total factor productivity, Icrier studied 1,553 firms that have some software investment. What it found was that there was a huge gap in the use of AI, suggesting a large untapped potential. AI-intensity was defined as the ratio of software investment to total sales, and the study found that, for instance, in the case of agriculture, while the average AI intensity is 0.001, the maximum intensity was 20 times as much. For electrical and optical equipment manufacturing, the difference between the average and the top in the industry was 145-times; it was 742 in the case of trade and in the case of services, the average intensity was 0.159, while the maximum intensity was 110.

The report, however, argues that businesses alone wont be able to push AI, the government will have to play a bigger role, by setting up a nodal AI agency to push for AI-adoption and also drive business, government and academia partnerships. Another suggestion is to initiate large-scale skill development programmes to get the workforce ready for AI-adoption. What is worrying, however, is the slow pace of digital adoption so far, though the pandemic has helped speed up things a big; both the education and health sector, for instance, are likely to see faster adoption of AI techniques. A related problem is that of cybersecurity where India needs both a national strategy and a governance structure that is more well-defined.

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The AI-boost: Using more artificial intelligence will boost GDP growth - The Financial Express

AI applied to tumor microscopy images detects patterns of 167 different mutations and predicts patient survival in 28 cancer types

Researchers at EMBLs European Bioinformatics Institute (EMBL-EBI), the Wellcome Sanger Institute, Addenbrookes Hospital in Cambridge, UK, and collaborators have developed an artificial intelligence (AI) algorithm that uses computer vision to analyze tissue samples from cancer patients. They have shown that the algorithm can distinguish between healthy and cancerous tissues, and can also identify patterns of more than 160 DNA and thousands of RNA changes in tumors. The study, published in Nature Cancer, highlights the potential of AI for improving cancer diagnosis, prognosis, and treatment.

Cancer diagnosis and prognosis are largely based on two main approaches. In one, histopathologists examine the appearance of cancer tissue under the microscope. In the other, cancer geneticists, analyze the changes that occur in the genetic code of cancer cells. Both approaches are essential to understand and treat cancer, but they are rarely used together.

Clinicians use microscopy slides for cancer diagnosis all the time. However, the full potential of these slides hasnt been unlocked yet. As computer vision advances, we can analyze digital images of these slides to understand what happens at a molecular level, says Yu Fu, Postdoctoral Fellow in the Gerstung Group at EMBL-EBI.

Computer vision algorithms are a form of artificial intelligence that can recognize certain features in images. Fu and colleagues repurposed such an algorithm developed by Google originally used to classify everyday objects such as lemons, sunglasses and radiators to distinguish various cancer types from healthy tissue. They showed that this algorithm can also be used to predict survival and even patterns of DNA and RNA changes from images of tumor tissue.

Teaching algorithms to detect molecular changes

Previous studies have used similar methods to analyze images from single or a few cancer types with selected molecular alterations. However, Fu and colleagues generalized the approach on an unprecedented scale: they trained the algorithm with more than 17 000 images from 28 cancer types collected for The Cancer Genome Atlas, and studied all known genomic alterations.

What is quite remarkable is that our algorithm can automatically link the histological appearance of almost any tumor with a very broad set of molecular characteristics, and with patient survival, explains Moritz Gerstung, Group Leader at EMBL-EBI.

Overall, their algorithm was capable of detecting patterns of 167 different mutations and thousands of gene activity changes. These findings show in detail how genetic mutations alter the appearance of tumor cells and tissues.

Another research group has independently validated these results with a similar AI algorithm applied to images from eight cancer types. Their study was published in the same issue of Nature Cancer.

A potential tool for personalized medicine

The integration of molecular and histopathological data provides a clearer picture of a tumors profile. Detecting the molecular features, cell composition, and survival associated with individual tumors would help clinicians tailor appropriate treatments to their patients needs.

From a clinicians point of view, these findings are incredibly exciting. Our work shows how artificial intelligence could be used in clinical practice, explains Luiza Moore, Clinician Scientist and Pathologist at the Wellcome Sanger Institute and Addenbrookes Hospital. While the number of cancer cases is increasing worldwide, the number of pathologists is declining. At the same time, we strive to move away from the one size fits all approach and into personalized medicine. A combination of digital pathology and artificial intelligence can potentially alleviate those pressures and enhance our practice and patient care.

Sequencing technologies have propelled genomics to the forefront of cancer research, yet these technologies remain inaccessible to most clinics around the world. A possible alternative to direct sequencing would be to use AI to emulate a genomic analysis using data that is cheaper to collect, like microscopy slides.

Getting all that information from standard tumor images in a completely automatic manner is revolutionary, says Alexander Jung, PhD student at EMBL-EBI. This study shows what might be possible in the coming years, but these algorithms will have to be refined before clinical implementation.

Source article:

FU, Y., et al. (2020). Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis, Nature Cancer. Published online 27 07; DOI: 10.1038/s43018-020-0085-8

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But knowing what a difference their support can make (home court advantage, anyone?) the NBA is proposing a few solutions: a tap-to-cheer app and video technology that will teleport their faces court-side from the comfort of their homes.

"It's obviously very different for the players and it's different for the fans watching at home. I mean, in this sport -- like a lot of others -- there's that home court advantage, that six-man. It's the roar of the crowd, the boos of the crowd," said NBA commissioner Adam Silver Wednesday on CNN with Wolf Blitzer. "We are trying to replicate that to a certain extent without piping in obvious crowd noise."

It's still unclear what kind of difference this technology will make in the overall atmosphere of a sporting match, though.

Not every attempt has been successful, though.

In South Korea, FC Seoul was fined 100 million Korean won (around $81,000) after being accused of placing sex dolls in its stands to add to the atmosphere during a closed match.

CNN's Jack Guy contributed to this report.

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The NBA will use artificial intelligence and a tap-to-cheer app feature to help fans stuck at home get in the game - CNN

File photo of Tesla CEO Elon Musk. (Image credits: Reuters)

Tesla and SpaceX CEO Elon Musk has claimed that Artificial Intelligence will be 'vastly smarter' than any human and would overtake us by 2025.

"We are headed toward a situation where AI is vastly smarter than humans. I think that time frame is less than five years from now. But that doesn't mean that everything goes to hell in five years. It just means that things get unstable or weird," Musk said in an interview with New York Times over the weekend.

This is not the first time that Musk has shown concern related to AI. Back in 2016, Musk said that humans risk being treated like house pets by AI unless technology is developed that can connect brains to computers.

He even described AI as an 'existential threat' to humanity.

"I think we should be very careful about artificial intelligence. If I were to guess like what our biggest existential threat is, it's probably that,'' he said.

However, Musk helped found the artificial intelligence research lab OpenAI in 2015 with the goal of developing artificial general intelligence (AGI) that can learn and master several disciplines.

Recently, OpenAI released its first commercial product, a programme to make use of a text-generation tool that it once called too dangerous.

It has the potential to spare people from writing long texts. Once an application is developed on the basis of the programme, all they need to give is a prompt.

OpenAI earlier desisted from revealing more about the software fearing bad actors might misuse it for producing misleading articles, impersonate others or even automate phishing content.

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Elon Musk Thinks that Artificial Intelligence Will Be 'Vastly Smarter' Than Humans in 5 Years - News18

Artificial Intelligence acts as a potential key technology of dystopian future concepts, social control, and autocratic world power fantasies. It is gradually finding its way to the public and private board room discussions and government policies. Even countries like Germany, which were lagging in the AI race, have gone through tremendous change in the past few years. According to PwC research, by 2030, Germany alone shall have Gross Domestic Product (GDP) up by 11.3% and generate 430 billion due to AI. And by percentage, this potential is more than most of the other European Nations. This makes the country as Europes largest economy, with a thriving market and high potential for new to market brands. The study also that industries like healthcare, energy, and the auto industry will benefit from significant productivity gains by adopting AI applications.

While Germany is currently at the forefront of AI in Europe, research and innovative projects have also commenced in the Cyber Valley. The goal is to further the mission to develop increasingly sophisticated machines with extensive capabilities and boost R&D in AI. Founded just four years ago by the Max Planck Institute for Intelligent Systems (MPII) together with auto groups Bosch, Daimler, BMW, and Porsche, the cluster had also secured 1.25 million investment from Amazon for research partnership. The main motive behind this initiative is to leverage AI to make theGerman industries, services, and products even better. Germany is also striving to bring the digital revolution through Industry 4.0, which was also mentioned in the AI strategy of 2018. The strategy report further expresses that the country shall expand its strong position and rise to be a global leader in AI on the grounds of ethics and legal terms too. It also intends to use AI to promote social participation, freedom of action, and self-determination for citizens and foster the sustainable development of the society. To achieve this goal, the Federal Government first allocated a total of 500 million to beef up the AI strategy for 2019 and further anticipates matching funds from the private sector and other the federal states, therefore bringing the total investment to 6 billion.

Meanwhile, the emphasis is also made on improving data sharing facilities by providing open access to governmental data. The government is also working to build a reliable data and analysis infrastructure based on cloud platforms and upgraded storage and computing capacity. These measures are crucial and necessary as, without data, AI innovations cannot be used to solve the bottlenecks and other issues faced by different industries in their quest for AI adoption. Recently, Germany is looking for ways to tighten data security. It is calling for a more concrete definition when data records must be stored on a mandatory basis. At the European Union, it has also requested for developing a new classification scheme together with the member states.

On the business front, tests are carried to maximize the use of collaborative AI robots and link augmented reality technology to AI-based production planning systems. Major automobile behemoths Volkswagen, BMW, and Daimler, are investing heavily in modern, AI-controlled factories. They are working on solutions for assisted and autonomous driving, intelligent operating systems, entertainment systems, and navigation systems at their German R&D centers.

Germany is also growing as a preferred hub for startups focusing on AI and its applications like machine learning, deep learning, computer vision, predictive analysis, and so on. Further, it has the most active corporate venture investors in Europe (91% of all non-IPO exitsin 2019 were related to corporates). The most common areas of focus for these AI startups are software development, image recognition, customer support and communication, and marketing and sales. These five categories are found to constitute around 48% of German AI startups. Currently, Berlin is the fourth largest global AI hub, following Silicon Valley of the USA, London, and Paris. So, it is high time that companies take Germany as an upcoming nation in global AI leadership and start investing or collaborating with it.

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A Brief Outlook on the Artificial Intelligence landscape in Germany - Analytics Insight