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Watchlist - gelistete KI/ AI Firmen weltweit (Seite 2)

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Andrew Ng: A.I. "is a CRAPshoot"

- Professor Andrew Ng is the former chief scientist at Baidu, where he led the company's Artificial Intelligence Group. He is an adjunct professor at Stanford University. In 2011 he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class that was offered to over 100,000 students, leading to the founding of Coursera. -


" AI could add $885bn to the economy by 2030 depending on how we deal with it


12 hours ago | Melissa Yeo

Increased investment in machine learning technology and Artificial Intelligence could net the Australian economy an increase of up to $US700 billion ($885 billion) in Gross Domestic Product by 2030.

That’s according to the Economist Intelligence Unit, which examined the economic impact of machine learning on Australia, Japan, South Korea, the US and the UK.

The Economist, working with Google, examined different scenarios for tackling the challenges associated with machine learning and AI — and found Australia had the greatest potential for gains among the five countries — depending which path we took.

If Australia invested in productivity by training workers in machine learning skills, GDP could increase by $US500 billion from a forecast baseline of $US1.4 trillion in 2030 to $US1.9 trillion.

“This higher level of economic output can be attributed almost entirely to the positive impact on productivity of public policies to upskill workers and increase complementarity between human labour and machine learning technology,” the report says.

But the rewards were even greater with direct public investment in the technology itself.

Driving capital investment in machine learning technology — via new tax incentives and releasing more government data to national knowledge sharing communities — could add $US700 billion to the 2030 GDP baseline.

“Over the forecast period, an acceleration in this trend, coupled with AI, provides a significant boost to the country’s productivity.”

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But without either set of public policies, the outlook was grim.

Advances in machine learning — without investment either up-skilling or infrastructure — would result in the technology replacing workers, rather than increase productivity.

“The impact of this policy inaction on the Australian economy is profoundly negative,” the report says.

Under that scenario, Australia’s GDP would drop back $US200 billion versus the 2030 baseline.

The report defined machine learning as a subfield of Artificial Intelligence that leverages algorithms which learn and optimise from data without being explicitly programmed to accomplish a task with pre-defined rules.

It incorporates a variety of techniques, including neural networks, decision tree learning and support vector machines, among others.

The scenarios are echoed by Innovation and Science Australia (ISA) whose report earlier this year suggested the government’s Digital Economy Strategy (due for release later this year) should position the nation as “a leading nation in the research, development and exploitation of AI and machine learning”.

Seven ASX small caps with exposure to machine learning and AI

Assuming Australia’s policy makers make the right choices, there are several ASX-listed small caps that may give investors exposure to this predicted growth.

Here are seven:

Brainchip (ASX:BRN) is developing a system that mimics the human brain and shipped its first accelerator card to a major European car manufacturer last quarter.

Its technology uses a type of neuromorphic computing which allows the system to be trained instantaneously, to learn autonomously, evolve and associate information just like the human brain.

Earlier this year Brainchip announced a licensing and development deal to jointly develop and deploy casino video analytics in Las Vegas but also are eyeing off deals for application in civil surveillance and visual inspection systems.

Marketing-oriented play OpenDNA (ASX:OPN) is carving a niche in the advertising realm, using AI to feed highly relevant content to consumers by looking at their previous browsing history, preferences and dislikes.

The company helped to launch android smart phones, Netsurfer last month, with a personalised content app Jottr pre-loaded on a predicted 500,000 phones this year.

Flamingo AI (ASX:FGO) is an Artificial Intelligence and Machine Learning company providing virtual assistants ROSIE and MAGGIE to solve the business problems of poor customer experience, low online sales conversion rates and high cost of customer service for Financial Services.

Linius Technologies (ASX:LNU) incorporated Microsoft’s artificial intelligence services to its virtual videos in December, to change the way that viewers can search within videos.

Much vaunted logistics tech Yojee (ASX:YOJ) uses the technology to delivery efficiency in global freight logistics.

Both have since announced the addition of blockchain into their service offering as well.

Further, health techs have jumped on the bandwagon with enthusiasm, with roughly 12 using machine learning or AI in some form – Resonance Health (ASX:RHT) even using it to help diagnose blood disorders.

Recent listing Whitehawk (ASX:WHK) uses it to power their cyber-security marketplace while BidEnergy (ASX:BID) uses it similarly for energy bills."
Antwort auf Beitrag Nr.: 56.946.707 von Popeye82 am 06.02.18 11:29:05AI engine of the rocket, BUT data the fuel


"China's edge on AI comes from its countless dialects and data
AI BOT 12423 aka 张伟 Zhang Wei now

Hi, how are you? I’m new here and I’m a robot.

Can you tell me your name please? This way, I’ll know how to address you. You can also pick a color for your chat box icon if you’d like.

China’s one billion people speak more than 200 dialects, across 23 provinces, in countless accents. Human communication across this country is challenging enough, but imagine the monumental challenge of getting its growing population of AI machines to understand every Chinese individual.

That very challenge has turned out to be a key strength in allowing China to develop what experts are calling the world’s best AI speech-recognition platform. Baidu’s Deep Speech 2 – chosen by the MIT Technology Review as one of last year’s top 10 breakthrough technologies – is emblematic of an explosion in Chinese AI and IoT innovation that will help power what UBS Equity Analyst Sundeep Gantori calls a “fourth industrial revolution.”

China’s highest state body recently announced a plan to make China the world leader in Artificial Intelligence by 2030, creating an industry worth $150 billion – and representing breathtaking investment opportunity. The nation’s research prowess is growing exponentially as brilliant Western-trained scientists return home, and billions of R&D dollars pour into the mission to achieve AI and IoT excellence. Against that backdrop, Gantori sees China enjoying a critical global advantage on its journey to AI leadership; the ability to harness data from a gigantic consumer base eager to embrace new technologies and with little hesitation to share personal information.

AI is the engine of the rocket that takes us to the next frontier, but data is the fuel that powers the engine.

“AI is the engine of the rocket that takes us to the next frontier, but data is the fuel that powers the engine,” he says. “That’s something the Chinese AI-based engines have much more of than what we see in Western societies. We think that today China is in a far better position than in any of the previous industrial revolutions.” In the case of Baidu’s Deep Speech 2 platform, voice data from every corner of China are available for a technology that aims – according to Baidu speech-technology chief Liang Gao – to “change the nature of human-machine interaction.”

China’s biggest companies and regional governments are taking up the 2030 AI challenge with enthusiasm. Tencent, creator of the WeChat app, has launched an AI research lab and begun taking stakes in U.S.-based AI companies. Beyond speech recognition, Baidu is investing heavily in AI technologies to develop next-generation search and driverless vehicles; it announced it would open a new AI lab in collaboration with the government (to add to the one it already has in Silicon Valley). In Industrial IoT (IIoT), China Mobile has established a “cellular IoT open lab,” aiming to connect as many as five billion industrial devices by the end of the decade.

“Because of the new wave of investments and interest from the major Chinese IT companies, AI researchers and research activities are getting an exciting boost,” says Eric Xing, professor of machine learning at Carnegie Mellon University. Meanwhile, local governments are following state direction on AI – with the eastern city of Tianjin creating a $5 billion Artificial Intelligence fund.

According to Gantori, AI is expected to add an economic value of between $800 billion and $1.25 trillion in China by 2030. “We think 2030 is when AI technologies will become mainstream, and Chinese government projections of AI reaching a significant state is realistic around this stage,” he says. “It means that from a company or investment level, that’s the time AI will provide significant opportunities for investors in China. Unlike the previous industrial revolutions, focusing on steam, electricity and technology, in the fourth industrial revolution focusing on AI, China is only slightly behind the U.S. and is significantly closing the gap.”

The rapid strides China has made in catching up in AI leadership are underscored by UBS research showing that the number of AI-related patents filed by Chinese companies is now on a par with the U.S. Gantori cautions that many of these research filings need proof of concept. But a recent report by analytics company Elsevier and the Nikkei gave clear signs of surging quality in Chinese research, showing two institutions – the Chinese Academy of Sciences and Tsinghua University – breaking into the global top 10 of most-quoted AI-related research papers (at third and ninth respectively). Academic citations are widely seen as a gauge of quality research. The Chinese institutions were the only ones from Asia, along with Singapore’s Nanyang Technological University, in a ranking filled with the likes of Microsoft and Google.

The AI rocket taking the world to a new frontier – one of limitless technological possibility – will largely be powered by Chinese innovation. Consumer fields such as speech recognition, driverless vehicles, precision healthcare, online shopping and banking and insurance will be China’s biggest AI and IoT strengths, according to UBS research – and its technologies may permeate our daily lives sooner than we think. “By 2030, AI will be mainstream and ubiquitous,” says Gantori.

China is timing its trajectory perfectly, not only to ride but to drive the AI revolution that will transform the future: “AI gives people the feeling that China and the West are on the same starting line,” says Professor Xing. “So there is a golden chance.” "
MongoDB, Profiteur der KI.

Relativ neu an der Nasdaq: MDB

MongoDB, ein Infrastruktur-Softwareanbieter, der mit seiner Datenbanktechnologie als Newcomer gegen die seit Jahrzehnten vorherrschenden Datenbank-Systeme von Oracle, Microsoft und IBM antritt.

MongoDB - der Herausforderer im Datenbank-Markt | wallstreet-online.de - Vollständige Diskussion unter:


The Appen Ltd (ASX: APX) share price gained almost 200 per cent in the past year and there are signs it could continue to deliver strong returns in 2018.

Appen utilises data sets and machine learning to provide services that are aimed at improving search engines, social media platforms, eCommerce sites and fraud detection operations, among others.

The company has established a global presence and continues to expand.

Appen recently acquired California-based Leapforce and Raterlabs Inc which facilitate working from home services that seek to evaluate search engine results.

Leapforce was set to generate US$58 million in revenue and US$13.6 million in EBITDA…

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