« First «...10 20 30...1,146 1,1471,1481,149 1,150...1,160 1,170 1,180...»Last »

AI/Machine Learning Market Size by Top Key Players, Growth Opportunities, Incremental Revenue , Outlook and Forecasts to 2026 – Latest Herald

Posted on May 3, 2020 by admin

Amazon

Global AI/Machine Learning Market: Competitive Landscape

This section of the report lists various major manufacturers in the market. The competitive analysis helps the reader understand the strategies and collaborations that players focus on in order to survive in the market. The reader can identify the players fingerprints by knowing the companys total sales, the companys total price, and its production by company over the 2020-2026 forecast period.

Global AI/Machine Learning Market: Regional Analysis

The report provides a thorough assessment of the growth and other aspects of the AI/Machine Learning market in key regions, including the United States, Canada, Italy, Russia, China, Japan, Germany, and the United Kingdom United Kingdom, South Korea, France, Taiwan, Southeast Asia, Mexico, India and Brazil, etc. The main regions covered by the report are North America, Europe, the Asia-Pacific region and Latin America.

The AI/Machine Learning market report was prepared after various factors determining regional growth, such as the economic, environmental, technological, social and political status of the region concerned, were observed and examined. The analysts examined sales, production, and manufacturer data for each region. This section analyzes sales and volume by region for the forecast period from 2020 to 2026. These analyzes help the reader understand the potential value of investments in a particular country / region.

We Offer up to 30% Discount @ https://www.marketresearchintellect.com/ask-for-discount/?rid=193669&utm_source=LHN&utm_medium=888

Key Benefits for Stakeholders:

The report provides an in-depth analysis of the size of the AI/Machine Learning world market, as well as recent trends and future estimates, in order to clarify the upcoming investment pockets.

The report provides data on key growth drivers, constraints and opportunities, as well as their impact assessment on the size of the AI/Machine Learning market.

Porters 5 Strength Rating shows how effective buyers and suppliers are in the industry.

The quantitative analysis of the AI/Machine Learning world industry from 2020 to 2026 is provided to determine the potential of the AI/Machine Learning market.

This AI/Machine Learning Market Report Answers To Your Following Questions:

Who are the main global players in this AI/Machine Learning market? What is the profile of your company, its product information, its contact details?

What was the status of the global market? What was the capacity, the production value, the cost and the profit of the market?

What are the forecasts of the global industry taking into account the capacity, the production and the value of production? How high is the cost and profit estimate? What will be the market share, supply, and consumption? What about imports and export?

What is market chain analysis by upstream raw materials and downstream industry?

Get Complete Report @ https://www.marketresearchintellect.com/need-customization/?rid=193669&utm_source=LHN&utm_medium=888

About Us:

Market Research Intellect provides syndicated and customized research reports to clients from various industries and organizations with the aim of delivering functional expertise. We provide reports for all industries including Energy, Technology, Manufacturing and Construction, Chemicals and Materials, Food and Beverage and more. These reports deliver an in-depth study of the market with industry analysis, market value for regions and countries and trends that are pertinent to the industry.

Mr. Steven Fernandes

Market Research Intellect

New Jersey ( USA )

Tel: +1-650-781-4080

Tags: AI/Machine Learning Market Size, AI/Machine Learning Market Trends, AI/Machine Learning Market Growth, AI/Machine Learning Market Forecast, AI/Machine Learning Market Analysis

See the article here:
AI/Machine Learning Market Size by Top Key Players, Growth Opportunities, Incremental Revenue , Outlook and Forecasts to 2026 - Latest Herald

How AI and ML in the networking domain strengthens security – CISO MAG

Posted on May 3, 2020 by admin

In 2004, a few unmanned vehicles showed up at the starting gate of the lengthy course across the Mojave Desert this was the inaugural DARPA Grand Challenge. It signified the beginning of the technological race to develop a practical self-driving car, which sparked a global movement that continues even today.

The networking community too embarked on a similar journey to provide production-ready, economically feasible, Self-Driving Networks. Self-Driving Networks are autonomous networks that use Artificial Intelligence (AI) and Machine Learning (ML) to program independently and carry out prescribed intentions while eliminating complex programming and management tasks required today to run the networks. In view of this, the proliferation of data breaches and cyberattacks in todays networking environment has also increased, leading to extensive repercussions across businesses. As such, ML-based security solutions have become a major cybersecurity investment for organizations today.

By Rohit Sawhney Systems Engineering Manager at Juniper Networks India

Many experts believe that AI and ML will dominate cybersecurity in the future. Last year, at the Gartner IT Symposium/Xpo, analysts discussed how these two technologies will augment human decision-making, emotions, and relationships.

Rapid technological advances are enabling AI to disrupt the networking industry with new insights and automation. AI in the networking domain will be able to reduce IT costs and offer the best possible user experience. Not only will AI be able to reduce IT costs, but it will also bring in more productivity and efficiency in networking. Together, machine learning and AI could be key enablers, helping to reduce human effort and make cybersecurity faster, more consistent and accurate.

In fact, many Enterprises are already making greater investments to integrate solutions with machine learning algorithms into their existing security infrastructure. While traditional antivirus programs are still widely used to detect and neutralize threats, they do not have the capability to detect and mitigate sophisticated threats. ML-based security solutions like the Juniper ATP can help monitor potential threats in the network through threat intelligence features allowing IT security teams to detect any suspicious activity before the attack occurs.

AI comes to the rescue as it reduces the number of monotonous tasks that take up an engineers time, while ensuring they are always completed accurately, regardless of frequency and quantity. This allows engineers to focus on other business strategic tasks while maintaining network health and safety.

In a recent survey conducted by KPMG for its report, Living in an AI World 2020, analysts found that 92% of respondents agree that leveraging spectrum of AI technologies will make their companies run more efficiently. However, in the networking domain, IT simply cant meet the needs of todays stringent network requirements, without a robust AI strategy. The following are some technology elements that an AI strategy should include:

ML a subset of AI, is a prerequisite for any successful deployment of AI technologies. ML uses algorithms to parse data, learn from it, and determines or predicts without requiring explicit instructions. With that said, AI/ML can be leveraged for the following tasks in the networking domain:

About the Author

Rohit Sawhney is a Systems Engineering Manager at Juniper Networks India. He leads the team of Technical Consultants supporting Junipers North/East India & SAARC business. Prior to joining Juniper Networks, he has worked with IBM India and has industry experience of over 20 years. Rohit is a certified by Juniper Networks, Cisco and VMWare. He holds a masters degree in Computer Application from Sikkim Manipal University of Health, Medical and Technological Sciences and a Bachelors of Science in Electronics from Delhi University.

Disclaimer

CISO MAG did not evaluate/test the products mentioned in this article, nor does it endorse any of the claims made by the writer. The facts, opinions, and language in the article do not reflect the views of CISO MAG and CISO MAG does not assume any responsibility or liability for the same. CISO MAG does not guarantee the satisfactory performance of the products mentioned in this article.

Read more from the original source:
How AI and ML in the networking domain strengthens security - CISO MAG

AI Weekly: Animal Crossing, ICLR, and the future of research conferences online – VentureBeat

Posted on May 3, 2020 by admin

This week, the worlds machine learning community got a good look at what digital research conferences will look like in a post-coronavirus future, as ICLR kicked off whats believed to be the first major AI research conference held entirely online. The conference was initially scheduled to be held in person in Addis Ababa, Ethiopia. The Computer Vision and Pattern Recognition (CVPR) conference is next month and will be partially or entirely digital, while ICML, one of the biggest annual AI research conferences in the world, will be held entirely online in July.

Also this week: An NLP researcher announced plans to host the first-ever AI workshop inside Nintendos Animal Crossing: New Horizons this July. Artie lead scientist Josh Eisenberg told VentureBeat that more than 200 people have already signed up to watch the day-long event. Animal Crossing: New Horizons launched March 20 and is now the best-selling game in the U.S. and third-best launch of any game in Nintendo history.

One major area of focus for each event is figuring out how to create social connections. Thats part of what motivated an Animal Crossing AI workshop.

I was talking to my fiance about social interactions and quarantine, and some of our deepest interactions with other people over the past couple of months have been via video games, specifically with our friends in Animal Crossing. So I wanted to apply that to work and research to see if we can combine an academic-style workshop with the social interactions of Animal Crossing, Eisenberg said.

By contrast, the International Conference on Learning Representations (ICLR) may be the largest AI conference to take place entirely online. Each of the 680 papers was presented by authors via a prerecorded 5- or 15-minute talk. Every video was accompanied by recommendations for similar papers, something one attendee suggested should become the standard for all machine learning research conferences. There was also a paper search bar and visualization showing how each paper relates to each other to group similar works and make it easier to spot major areas of interest.

Many people are pondering the best ways to host digital events. Its something VentureBeat and other media brands are thinking about a lot internally as well. This week, VB ran its annual GamesBeat Summit event entirely online, and Transform, VBs annual AI conference, will take place online in July.

Three members of the VentureBeat AI team attended ICLR to check out innovative research in GANs like U-GAT-IT, NLP likeReformer, and neurosymbolic AI Iike Clevrer, as well as workshops on topics like climate change, affordable health care, and machine translation for African languages.

The entire weeks worth of ICLR keynote addresses and workshops were pre-recorded and available on the first day of the conference, so attendees could binge watch them or peruse them throughout the week. The advantage of tuning in to a given talk or workshop at its appointed time on the schedule was to get access to live Q&A with speakers and participate in the live chats that accompanied each session.

It appears theres no simple way to recreate the busy floor of a conference poster session today. Instead, each author attended live Q&A sessions with colleagues. A remarkable amount of online feedback was positive, but one ICLR attendee told VentureBeat they found some lack of participation in poster sessions. Since ICLR organizers only chose to convert to an all-digital conference last month, maybe posters sessions attendance improves when attendees know they can schedule time to talk about novel work or meet a favorite research author.

By going entirely digital, ICLR more than doubled participation from 2,700 in 2019 to 5,600 people from nearly 90 countries. There were more than 1,400 speakers and one million page views, and videos were watched more than 100,000 times, organizing committee general chair Sasha Rush wrote in a tweet.

Cutting the expense is another major plus. The Animal Crossing conference will run you the cost of Animal Crossing: New Horizons ($60) and a Nintendo Switch ($299). ICLR was $100 down from the $500 of an in-person ticket cost. Add in the cost of a plane ticket to Ethiopia, lodging, and meals, and the physical conference could have cost upwards of $2,000.

But a challenge for digital events going forward, it seems, is finding ways to connect people.

To try to re-create social gatherings, ICLR held social gatherings inside Zoom to discuss topics ranging from deep generative models to open source tools and risky research. Affinity groups like Latinx in AI and Queer in AI also held digital get-togethers.

A Medium post by a researcher who described social challenges includes comments from Rush, who said creating a flow at the conference akin to the in-person feel of flowing between posters and hallway chats was a challenge. I dont think we have totally figured that out yet, but it was fun trying to recreate virtual versions of these interactions, he said.

In a blog post in February, ICLR organizer Yoshua Bengio one of the most cited researchers in the world urged the machine learning community to begin thinking about and experimenting with how to make digital conferences work in digital environments. Bengio, who gave a keynote address at ICLR this week and did live Q&A with Turing Award winner Yann LeCun, first insisted on more digital offerings as a way to cut down on the machine learning communitys carbon footprint.

Experiments should begin now, Bengio said, in part to address the challenge of recreating social experiences on par with meeting in person or striking a balance. Some events could combine in-person attendance with digital, while conferences rapidly growing in popularity like NeurIPSmay host more regional events.

Invited speakers at the Animal Crossing workshop will present their work on one Animal Crossing island, but to inject impromptu meetings into the process, in between presentations attendees will get Dodo codes to go to coffee break islands to chat with about 5 people. Each island will have themes for people with similar interests, like computer vision or NLP, to discuss workshop subject matter or whatever else comes to mind. If 200 people show up, he expects to need around 50 islands. He said keeping track of attendee Dodo codes for interest-specific islands may be one of the biggest technical challenges to pulling off an Animal Crossing workshop.

Zoom, Twitch, Google Meet, or another service will be used to provide sound for speakers, as well as a way for people to watch presentations inside Animal Crossing whether or not they have the game.

Austin Parker organized theDeserted Island DevOps workshop, a similar event that took place in Animal Crossing Thursday and attracted thousands of viewers on Twitch. He told VentureBeat forming community to do things like organize hallway track side conversations was easy, but tasks like finding moderators in an extremely open community was a challenge.

Another potential challenge: Widespread Nintendo Switch shortages during the global COVID-19 pandemic.

Eisenberg said the Animal Crossing AI workshop (ACAI) is designed to be accessible to people who dont normally attend conferences and aims to be as fun as it is educational.

The draw for these conferences is the networking and the chance social interactions, not the raw knowledge. Like, a 20-minute presentation isnt going to teach you everything about an AI paper thats someone devoted a year of their life on thats not the point. Youre not there to go back to school, youre there to meet people and to talk and to share ideas in a social manner, so I think the social aspect of these things are the most important, he said.

To be clear: The Animal Crossing AI workshop and ICLR are very different kinds of gatherings. ICLR is organized by a group of machine learning community leaders. The Animal Crossing AI workshop is organized by one guy. But both demonstrate what online AI conferences, and indeed other scientific research communities, may look like.

The format for research conferences online is important because the work of scientific communities in machine learning and fields like health care and life sciences can influence which ideas and methods gain traction.

What ICLR and ACAI have in common is they reflect a collective need to connect and learn.

Nothing replaces being there. The ICLR conference, for example, was originally scheduled to take place in Ethiopia this year, and though African perspectives were put front and center in some conference content, theres no replacing being in that place. Being there also means you can stay in the moment. Keeping locked in for a week of online content can be tough.

It may be a long time before researchers have the pleasure of cramming into hotel conference rooms shoulder to shoulder again, but even if a cure for coronavirus arrives tomorrow, experiments in digital conference events particularly social aspects should continue as a way to increase access, lower barriers, and bring more people into the process.

For AI coverage, send news tips to Khari Johnson and Kyle Wiggers and AI editor Seth Colaner and be sure to subscribe to the AI Weekly newsletter and bookmark our AI Channel.

Thanks for reading,

Khari Johnson

Senior AI Staff Writer

Machine Learning Artificial intelligence Market 2020, Thrives the Growth at Impressive CAGR Over Forecast Period 2027 COVID-19 Impact on Global…

Posted on May 3, 2020 by admin

TheMachine Learning Artificial intelligenceMarketResearch Report offers an extensive analysis of key drivers, leading market players, key segments, and regions. Besides this, the experts have deeply studied different geographical areas and presented a competitive scenario to assist new entrants, leading market players, and investors to determine emerging economies. These insights offered in the report would benefit market players to formulate strategies for the future and gain a strong position in the global market.

Request For Sample Copy of Machine Learning Artificial intelligence Market Research Report

**The sample pages of this report is immediately accessible on-demand.**

Our Sample Report Covers-

The report covers present status and future prospects.

The report analyses market trends, size, and forecast in different geographically.

The report provides market competition overview among the Top companies.

The report provides a complete analysis of the current and emerging market trends and opportunities.

Top market players are profiled in this research study Are:AIBrain, Amazon, Anki, CloudMinds, Deepmind, Google, Facebook, IBM, Iris AI, Apple, Luminoso, and Qualcomm

Furthermore, the report also categorizes the Machine Learning Artificial intelligencemarket on the basis of types of products or services, application segments, end-user, regions, and others. Each of the segments growth is assessed along with their growth estimation in the forecast period. Also, the Machine Learning Artificial intelligencemarket provides a scrupulous study on sales volume, industry size, shares, demand & supply analysis, and value analysis of several firms together with segmental analysis, relating to important geographies.

The report begins with a brief introduction and market overview of the Machine Learning Artificial intelligenceIndustry followed by its market scope and size. Next, the report provides an overview of market segmentation such as type, application, and region. The drivers, limitations, and opportunities for the market are also listed, along with current trends and policies in the industry.

The report provides a detailed study of the growth rate of every segment with the help of charts and tables. Furthermore, various regions related to the growth of the market are analyzed in the report. These regions include the USA, Europe, Japan, China, India, South East Asia, Central, and South America, Middle East and Africa, Other Regions. Besides this, the research demonstrates the growth trends and upcoming opportunities in every region.

Analysts have revealed that the Machine Learning Artificial intelligencemarket has shown several significant developments over the past few years. The report offers sound predictions on market value and volume that can be beneficial for the market players, investors, stakeholders, and new entrants to gain detailed insights and obtain a leading position in the market. Additionally, the report offers an in-depth analysis of key market players functioning in the global Machine Learning Artificial intelligenceIndustry.

The research presents the performance of each player active in the Machine Learning Artificial intelligence. It also offers a summary and highlights the current advancements of each player in the market. This piece of data is a great source of study material for the investors and stakeholders interested in the market. In addition, the report offers insights on suppliers, buyers, and merchants in the market. Along with this, a comprehensive analysis of consumption, market share, and growth rate of each application is offered for the historic period.

The report clearly shows that the Machine Learning Artificial intelligenceIndustry has achieved remarkable progress since 2026 with numerous significant developments boosting the growth of the market. This report is prepared based on a detailed assessment of the industry by experts. To conclude, stakeholders, investors, product managers, marketing executives, and other experts in search of factual data on supply, demand, and future predictions would find the report valuable.

Some important key factors included in the report:

Summary of the Machine Learning Artificial intelligenceMarket major key players having major count in terms of end-user demands, restraining elements, revenue, sales, share & size.

Characteristics of Machine Learning Artificial intelligenceMarket including industry growth and restraining factors, the technological advancements, new upcoming growth opportunities, and emerging segments of the Machine Learning Artificial intelligenceMarket.

Other factors such as Machine Learning Artificial intelligenceMarket price, demand, supply, profit/loss, and the growth factor are broadly discussed in the market report.

Machine Learning Artificial intelligenceMarket size, share, growth factors analysis on regional and country level segments.

Market Trends, Drivers, Constraints, Growth Opportunities, Threats, Challenges, Investment Opportunities, and recommendations.

The Questions Answered by Pagers Market Report:

What are the Key Manufacturers, raw material suppliers, equipment suppliers, end-users, traders And distributors in Pagers Market?

What are Growth factors influencing Pagers Market Growth?

What are production processes, major issues, and solutions to mitigate the development risk?

What is the Contribution from Regional Manufacturers?

What are the Key Market segment, market potential, influential trends, and the challenges that the market is facing?

Explore Complete TOC/ Ask for Customization@https://www.reportsandmarkets.com/reports/global-machine-learning-artificial-intelligence-market-2019-by-company-regions-type-and-application-forecast-to-2024?utm_source=latestherald&utm_medium=15

**This report can be customized to meet the clients requirements. Please connect with our sales team, to customize your report according to research needs.**

Few Points FromTable of Content:

1 Study Coverage

2 Executive Summaries

3 Breakdown Data by Manufacturers

4 Breakdown Data by Type

5 Breakdown Data by Application

6 North America

7 Europe

8 Asia Pacific

9 Central & South America

Applications

10 Middle East and Africa

11 Company Profiles

12 Future Forecast

13 Market Opportunities, Challenges, Risks and Influences Factors Analysis

14 Value Chain and Sales Channels Analysis

15 Research Findings and Conclusion

16 Appendix

About us

Market research is the new buzzword in the market, which helps in understanding the market potential of any product in the market. This helps in understanding the market players and the growth forecast of the products and so the company. This is where market research companies come into the picture. Reports And Markets is not just another company in this domain but is a part of a veteran group called Algoro Research Consultants Pvt. Ltd. It offers premium progressive statistical surveying, market research reports, analysis & forecast data for a wide range of sectors both for the government and private agencies all across the world.

Contact Person

Sanjay Jain

Manager Partner Relations & International Marketing

http://www.reportsandmarkets.com

Ph: +1-352-353-0818 (US)

View original post here:
Machine Learning Artificial intelligence Market 2020, Thrives the Growth at Impressive CAGR Over Forecast Period 2027 COVID-19 Impact on Global...

When quantum computing and AI collide – Raconteur

Posted on May 2, 2020 by admin

Machine-learning and quantum computing are two technologies that have incredible potential in their own right. Now researchers are bringing them together. The main goal is to achieve a so-called quantum advantage, where complex algorithms can be calculated significantly faster than with the best classical computer. This would be a game-changer in the field of AI.

Such a breakthrough could lead to new drug discoveries, advances in chemistry, as well as better data science, weather predictions and natural-language processing. We could be as little as three years away from achieving a quantum advantage in AI if the largest players in the quantum computing space meet their goals, says Ilyas Khan, chief executive of Cambridge Quantum Computing.

This comes after Google announced late last year that it had achieved quantum supremacy, claiming their quantum computer had cracked a problem that would take even the fastest conventional machine thousands of years to solve.

Developing quantum machine-learning algorithms could allow us to solve complex problems much more quickly. To realise the full potential of quantum computing for AI, we need to increase the number of qubits that make up these systems, says Dr Jay Gambetta, vice president of quantum computing at IBM Research.

Quantum devices exploit the strange properties of quantum physics and mechanics to speed up calculations. Classical computers store data in bits, as zeros or ones. Quantum computers use qubits, where data can exist in two different states simultaneously. This gives them more computational fire power. Were talking up to a million times faster than some classical computers.

And when you add a single qubit, you double the quantum computers processing power. To meet Moores Law [the number of transistors on a computer chip is doubled about every two years while the cost falls], you would need to add a single qubit every year, says Peter Chapman, chief executive of IonQ.

Our goal is to double the number of qubits every year. We expect quantum computers to be able to routinely solve problems that supercomputers cannot, within two years.

Already industrial behemoths, such as IBM, Honeywell, Google, Microsoft and Amazon, are active in the quantum computing sector. Their investments will have a major impact on acceleratingdevelopments.

We expect algorithm development to accelerate considerably. The quantum community has recognised economic opportunities in solving complex optimisation problems that permeate many aspects of the business world. These range from how do you assemble a Boeing 777 with millions of parts in the correct order? to challenges in resource distribution, explains Dr David Awschalom, professor of quantum information at the University of Chicago.

The quantum community has recognised economic opportunities in solving complex optimisation problems that permeate many aspects of the business world

Many of the computational tasks that underlie machine-learning, used currently for everything from image recognition to spam detection, have the correct form to allow a quantum speed up. Not only would this lead to faster calculations and more resource-efficient algorithms, it could also allow AI to tackle problems that are currently unfeasible because of their complexity and size.

Quantum computers arent a panacea for all humankinds informatic problems. They are best suited to very specific tasks, where there are a huge number of variables and permutations, such as calculating the best delivery route for rubbish trucks or the optimal path through traffic congestion. Mitsubishi in Japan and Volkswagen in Germany have deployed quantum computing with AI to explore solutions to these issues.

There will come a time when quantum AI could be used to help us with meaningful tasks from industrial scheduling to logistics. Financial optimisation for portfolio management could also be routinely handled by quantum computers.

This sounds like it might have limited use, but it turns out that many business problems can be expressed as an optimisation problem. This includes machine-learning problems, says Chapman.

Within a few short years we will enter the start of the quantum era. Its important for people to be excited about quantum computing; it allows government funding to increase and aids in recruitment. We need to continue to push the technology and also to support early adopters to explore how they can apply quantum computing to their businesses.

However, its still early days. The next decade is a more accurate time frame in terms of seeing quantum computing and AI coalesce and really make a difference. The need to scale to larger and more complex problems with real-world impact is one area of innovation, as is creating quantum computers that have greater precision and performance.

The limitation of quantum technology, particularly when it comes to AI, is summarised by the term decoherence. This is caused by vibrations, changes in temperature, noise and interfacing with the external environment. This causes computers to lose their quantum state and prevents them from completing computational tasks in a timely manner or at all, says Khan.

The industrys immediate priority has shifted from sheer processing power, measured by qubits, to performance, better measured by quantum volume. Rightly so the industry is channelling its energy into reducing errors to break down this major barrier and unlock the true power of machine-learning.

Over time it is the ease of access to these computers that will lead to impactful business applications and the development of successful quantum machine-learning. IBM has opened its doors to its quantum computers via the cloud since 2016 for anyone to test ideas. In the process it has fostered a vibrant community with more than 200,000 users from over 100 organisations.

The more developers and companies that get involved in first solving optimisation problems related to AI and then over time building quantum machine-learning and AI development, the sooner well see even more scalable and robust applications with business value, explains Murray Thom, vice president of software at D-Wave Systems.

Most importantly, we need a greater number of smart people identifying and developing applications. That way we will be able to overcome limitations much faster, and expand the tools and platform so they are easier to use. Bringing in more startups and forward-thinking enterprise organisations to step into quantum computing and identify potential applications for their fields is also crucial.

Continue reading here:
When quantum computing and AI collide - Raconteur

Devs: Here’s the real science behind the quantum computing TV show – New Scientist News

Posted on May 2, 2020 by admin

By Rowan Hooper

BBC/FX Networks

TVDevsBBC iPlayer and FX on Hulu

Halfway through episode two of Devs, there is a scene that caused me first to gasp, and then to swear out loud. A genuine WTF moment. If this is what I think it is, I thought, it is breathtakingly audacious. And so it turns out. The show is intelligent, beautiful and ambitious, and to aid in your viewing pleasure, this spoiler-free review introduces some of the cool science it explores.

Alex Garlands eight-part seriesopens with protagonists Lilyand Sergei, who live in a gorgeous apartment in San Francisco. Like their real-world counterparts, people who work atFacebook orGoogle, the pair take the shuttle bus to work.

They work at Amaya, a powerful but secretive technology company hidden among the redwoods. Looming over the trees is a massive, creepy statue of a girl: the Amaya the company is named for.

We see the company tag line asLily and Sergei get off the bus: Your quantum future. Is it just athrow-away tag, or should we think about what that line means more precisely?

Sergei, we learn, works on artificial intelligence algorithms. At the start of the show, he gets some time with the boss, Forest, todemonstrate the project he has been working on. He has managed to model the behaviour of a nematode worm. His team has simulated the worm by recreating all 302 of its neurons and digitally wiring them up. This is basically the WormBot project, an attempt to recreate a life form completely in digital code. The complete map of the connections between the 302 neurons of the nematode waspublished in 2019.

We dont yet have the processing power to recreate theseconnections dynamically in a computer, but when we do, it will be interesting to consider if the resulting digital worm, a complete replica of an organic creature, should be considered alive.

We dont know if Sergeis simulation is alive, but it is so good, he can accurately predict the behaviour of the organic original, a real worm it is apparently simulating, up to 10 seconds in thefuture. This is what I like about Garlands stuff: the show has only just started and we have already got some really deep questions about scientific research that is actually happening.

Sergei then invokes the many-worlds interpretation of quantum mechanics conceived by Hugh Everett. Although Forest dismisses this idea, it is worth getting yourhead around it because the show comes back to it. Adherents say that the maths of quantum physics means the universe isrepeatedly splitting into different versions, creating a vast multiverse of possible outcomes.

At the core of Amaya is the ultrasecretive section where thedevelopers work. No one outside the devs team knows what it is developing, but we suspect it must be something with quantum computers. I wondered whether the devssection is trying to do with the 86 billion neurons of thehuman brain what Sergei has been doing with the 302 neurons of the nematode.

We start to find out when Sergei is selected for a role in devs. He must first pass a vetting process (he is asked if he is religious, a question that makes sense later) and then he is granted access to the devs compound sealed by alead Faraday cage, gold mesh andan unbroken vacuum.

Inside is a quantum computer more powerful than any currently in existence. How many qubits does it run, asks Sergei, looking inawe at the thing (it is beautiful, abit like the machines being developed by Google and IBM). Anumber that it is meaningless to state, says Forest. As a reference point, the best quantum computers currently manage around 50 qubits, or quantum bits. We can only assume that Forest has solved the problem ofdecoherence when external interference such as heat or electromagnetic fields cause qubits to lose their quantum properties and created a quantum computer with fantasticprocessing power.

So what are the devs using it for? Sergei is asked to guess, and then left to work it out for himself from gazing at the code. He figures it out before we do. Then comes that WTF moment. To say any more will give away the surprise. Yet as someone remarks, the world is deterministic, but with this machine we are gaining magical powers. Devs has its flaws, but it is energising and exciting to see TV this thoughtful: it cast a spell on me.

Trump betting millions to lay the groundwork for quantum internet in the US – CNBC

Posted on May 2, 2020 by admin

In the 1960s the U.S. government funded a series of experiments developing techniques to shuttle information from one computer to another. Devices in single labs sprouted connections, then neighboring labs linked up. Soon the network had blossomed between research institutions across the country, setting down the roots of what would become the internet and transforming forever how people use information. Now, 60 years later, the Department of Energy is aiming to do it again.

The Trump administration's 2021 budget request currently under consideration by Congress proposes slashing the overall funding for scientific research by nearly 10% but boosts spending on quantum information science by about 20%, to $237 million. Of that, the DOE has requested $25 million to accelerate the development of a quantum internet. Such a network would leverage the counterintuitive behavior of nature's particles to manipulate and share information in entirely new ways, with the potential to reinvent fields including cybersecurity and material science.

Whilethetraditional internet for general useisn't going anywhere, a quantum networkwouldoffer decisive advantages for certain applications: Researchers could use it to develop drugs and materials by simulating atomic behavior onnetworked quantum computers, for instance, and financial institutions and governments would benefit from next-level cybersecurity. Many countries are pursuing quantum research programs, and with the 2021 budget proposal, the Trumpadministration seeks to ramp up thateffort.

"That level of funding will enable us to begin to develop the groundwork for sophisticated, practical and high-impact quantum networks," says David Awschalom, a quantum engineer at the University of Chicago. "It's significant and extremely important."

A quantum internet will develop in fits and starts, much like the traditional internet did and continues to do. China has already realized an early application, quantum encryption, between certain cities, but fully quantum networks spanning entire countries will take decades, experts say. Building it willrequire re-engineering the quantum equivalent of routers, hard drives, and computers from the ground up foundational work already under way today.

Where the modern internet traffics in bits streaming between classical computers (a category that now includes smart phones, tablets, speakers and thermostats), a quantum internet would carry a fundamentally different unit of information known as the quantum bit, or qubit.

Bits all boil down to instances of nature's simplest eventsquestions with yes or no answers. Computer chips process cat videos by stopping some electric currents while letting others flow. Hard drives store documents by locking magnets in either the up or down position.

Qubits represent a different language altogether, one based on the behavior of atoms, electrons, and other particles, objects governed by the bizarre rules of quantum mechanics. These objects lead more fluid and uncertain lives than their strait-laced counterparts in classical computing. A hard drive magnet must always point up or down, for instance, but an electron's direction is unknowable until measured. More precisely, the electron behaves in such a way that describing its orientation requires a more complex concept known as superposition that goes beyond the straightforward labels of "up" or "down."

Quantum particles can also be yoked together in a relationship called entanglement, such as when two photons (light particles) shine from the same source. Pairs of entangled particles share an intimate bond akin to the relationship between the two faces of a coin when one face shows heads the other displays tails. Unlike a coin, however, entangled particles can travel far from each other and maintain their connection.

Quantum information science unites these and other phenomena, promising a novel, richer way to process information analogous to moving from 2-D to 3-D graphics, or learning to calculate with decimals instead of just whole numbers. Quantum devices fluent in nature's native tongue could, for instance, supercharge scientists' ability to design materials and drugs by emulating new atomic structures without having to test their properties in the lab. Entanglement, a delicate link destroyed by external tampering, could guarantee that connections between devices remain private.

But such miracles remain years to decades away. Both superposition and entanglement are fragile states most easily maintained at frigid temperatures in machines kept perfectly isolated from the chaos of the outside world. And as quantum computer scientists search for ways to extend their control over greater numbers of finicky particles, quantum internet researchers are developing the technologies required to link those collections of particles together.

The interior of a quantum computer prototype developed by IBM. While various groups race to build quantum computers, Department of Energy researchers seek ways to link them together.

IBM

Just as it did in the 1960s, the DOE is again sowing the seeds for a future network at its national labs. Beneath the suburbs of western Chicago lie 52 miles of optical fiber extending in two loops from Argonne National Laboratory. Early this year, Awschalom oversaw the system's first successful experiments. "We created entangled states of light," he says, "and tried to use that as a vehicle to test how entanglement works in the real world not in a lab going underneath the tollways of Illinois."

Daily temperature swings cause the wires to shrink by dozens of feet, for instance, requiring careful adjustment in the timing of the pulses to compensate. This summer the team plans to extend their network with another node, bringing the neighboring Fermi National Accelerator Laboratory into the quantum fold.

Similar experiments are under way on the East Coast, too, where researchers have sent entangled photons over fiber-optic cables connecting Brookhaven National Laboratory in New York with Stony Brook University, a distance of about 11 miles. Brookhaven scientists are also testing the wireless transmission of entangled photons over a similar distance through the air. While this technique requires fair weather, according to Kerstin Kleese van Dam, the director of Brookhaven's computational science initiative, it could someday complement networks of fiber-optic cables. "We just want to keep our options open," she says.

Such sending and receiving of entangled photons represent the equivalent of quantum routers, but next researchers need a quantum hard drive a way to save the information they're exchanging. "What we're on the cusp of doing," Kleese van Dam says, "is entangled memories over miles."

When photons carry information in from the network, quantum memory will store those qubits in the form of entangled atoms, much as current hard drives use flipped magnets to hold bits. Awschalom expects the Argonne and University of Chicago groups to have working quantum memories this summer, around the same time they expand their network to Fermilab, at which point it will span 100 miles.

But that's about as far as light can travel before growing too dim to read. Before they can grow their networks any larger, researchers will need to invent a quantum repeater a device that boosts an atrophied signal for another 100-mile journey. Classical internet repeaters just copy the information and send out a new pulse of light, but that process breaks entanglement (a feature that makes quantum communications secure from eavesdroppers). Instead, Awschalom says, researchers have come up with a scheme to amplify the quantum signal by shuffling it into other forms without ever reading it directly. "We have some prototype quantum repeaters currently running. They're not good enough," he says, "but we're learning a lot."

Department of Energy Under Secretary for Science Paul M. Dabbar (left) sends a pair of entangled photons along the quantum loop. Also shown are Argonne scientist David Awschalom (center) and Argonne Laboratory Director Paul Kearns.

Argonne National Laboratory

And if Congress approves the quantum information science line in the 2021 budget, researchers like Awschalom and Kleese van Dam will learn a lot more. Additional funding for their experiments could lay the foundations for someday extending their local links into a country-wide network. "There's a long-term vision to connect all the national labs, coast to coast," says Paul Dabbar, the DOE's Under Secretary for Science.

In some senses the U.S. trails other countries in quantum networking. China, for example, has completed a 1,200-mile backbone linking Beijing and Shanghai that banks and other companies are already using for nearly perfectly secure encryption. But the race for a fully featured quantum internet is more marathon than sprint, and China has passed only the first milestone. Kleese van Dam points out that without quantum repeaters, this network relies on a few dozen "trusted" nodes Achilles' heels that temporarily put the quantum magic on pause while the qubits are shoved through bit-based bottlenecks. She's holding out for truly secure end-to-end communication. "What we're planning to do goes way beyond what China is doing," she says.

More from Tech Drivers:With America at home, Facebook, Google make moves to win more of gaming marketThe 87-year-old doctor who invented the rubella vaccine now working to fight the coronavirus

Researchers ultimately envision a whole quantum ecosystem of computers, memories, and repeaters all speaking the same language of superposition and entanglement, with nary a bit in sight. "It's like a big stew where everything has to be kept quantum mechanical," Awschalom says. "You don't want to go to the classical world at all."

After immediate applications such as unbreakable encryptions, he speculates that such a network could also lead to seismic sensors capable of logging the vibration of the planet at the atomic level, but says that the biggest consequences will likely be the ones no one sees coming. He compares the current state of the field to when electrical engineers developed the first transistors and initially used them to improve hearing aids, completely unaware that they were setting off down a path that would someday bring social media and video conferencing.

As researchers at Brookhaven, Argonne, and many other institutions tinker with the quantum equivalent of transistors, but they can't help but wonder what the quantum analog of video chat will be. "It's clear there's a lot of promise. It's going to move quickly," Awschalom says. "But the most exciting part is that we don't know exactly where it's going to go."

Continued here:
Trump betting millions to lay the groundwork for quantum internet in the US - CNBC

9 great reads from CNET this week – CNET

Posted on May 2, 2020 by admin

For the most up-to-date news and information about the coronavirus pandemic, visit the WHO website.

Alongsidepredictions that the coronavirus pandemiccould trigger the sharpest recession in the US since the Great Depression-- with consumer spending plummeting and unemployment at record highs -- it turns out big tech is doing ok. That was evident this week as companies reported mostly positive quarterly earnings.

Apple, for example, reported sales and profit growth, even as the pandemic weighs on iPhone demand. And Amazon sales surged even as CEO Jeff Bezos said coronavirus costs could hit $4 billion. Google also beat sales expectations and Facebook and Twitter both saw strong user growth amid the pandemic.

Meanwhile, Apple and Google are making progress on the coronavirus tracking tool they plan to release in mid-May. Also, the FDA on Friday made an emergency authorization for health care workers to use a promising drug called remdesivir to treat COVID-19.

Here are the week's stories you don't want to miss:

Quantum computing could help companies without billion-dollar budgets design superbatteries, create complex chemicals and understand the universe.

Deciding whether to trust memes and news stories is hard work.

Tracking the spread of infectious diseases like COVID-19 is more complex than following numbers. Memes and social media chatter matter too.

Never a hit with airlines and now grounded by the coronavirus pandemic, the still-young giant will disappear from the Airbus factory next year.

The author and illustrator reminds me of patience and working within limits.

FCC Commissioner Jessica Rosenworcel says the agency's report concluding that broadband is being delivered in a "reasonable and timely way" is wrong.

The ventilator uses parts that cost about $400 and can even be 3D-printed.

Ameelio Letters offers a free letter service to families of people who are incarcerated.

With its fall detection feature, heart rate notifications, exercise tracking and even the ability to make a call from your wrist, the Apple Watch has made a mark in each one of these stories.

See more here:
9 great reads from CNET this week - CNET

How to Get Bitcoins: 6 Tried-and-True Methods

Posted on May 2, 2020 by admin

Its a cliche, but, growing up, my Dad always preached about how theres no free lunch in life. If you want something valuable, you need to put in the work to earn it -- or spend money to buy it.

This timeless notion also applies to getting bitcoins. If you want to get a substantial amount of bitcoins fast, you need to spend money buying them. If you want to get a substantial amount of bitcoins for free, you need to spend a lot of time earning them on websites called bitcoin faucets.Expending monetary or mental resources to get bitcoins is a necessity. But some methods of buying and earning bitcoins are more effective than others. Read on to learn the best ways to buy bitcoins and the best ways to earn them for free through bitcoin faucets.

There are two ways you can get bitcoins:

To buy or earn free bitcoins, you first need to download a bitcoin wallet, which is software that allows you to securely send, receive, and store funds in the bitcoin network. There are four types of bitcoin wallets that you can use: mobile, web, desktop, and hardware.

Once you download a wallet, you need to set up an account on a cryptocurrency exchange thats approved by your wallet provider. Cryptocurrency exchanges are market places where sellers trade cryptocurrencies to buyers in exchange for fiat money or other digital currencies.

Most exchanges accept bank transfer or credit card payments, and some even accept Paypal payments. Theyll also charge you a transaction fee for every trade you make. You can choose from hundreds of crypto exchanges, but the most popular and reputable exchanges are Bitfinex, Bitstamp, Coinbase, and Coinmama. Heres a list of more popular crypto exchanges.

If youd rather buy bitcoins in person, you have four options to choose from:

One of the most entertaining and fun ways to earn free bitcoins is by playing mobile or online games. Thats right -- you can play games on your phone or computer and actually get paid in bitcoin.But if these bitcoin faucets want to make money and pay their players, they have to serve a lot of advertisements to their users.

To avoid the ads, you can join a bitcoin casino, where you bet your own money or bitcoin on traditional casino games, sports matches, and lotteries to potentially win a higher payout in bitcoin.

Heres a list of some of the most enjoyable bitcoin games that you can play on your phone.

Another way to earn free bitcoins is by completing tasks on websites. Some companies will pay you in Bitcoin to test their web sites, take their surveys, retweet their posts, and complete other small tasks.

There are also websites that let people offer small bitcoin rewards to the person who can give them the best answer to one of their questions.

You can find odd-jobs that pay you in Bitcoin on BitcoinGet, and you can answer questions for Bitcoin on Bitfortip.

Paying people to play simple games and complete repetitive jobs sounds like a great way attract a lot of users and, in turn, tons of advertisers. But there are hundreds of bitcoin faucets competing for users and advertisers attention, making it hard to stand out from the crowd.

Users also dont rely on faucets as a main source of income, so, a lot of the times, a small bitcoin reward isnt enough to coax them into doing boring tasks during their free time.

To generate more user activity and advertising revenue, bitcoin faucets, like Bitcoin Aliens, knew they needed to find a better way to engage their users. So they decided to pay people to read. Their service, PaidBooks, compensates people in Bitcoin to read classic books like Pride & Prejudice, War of the Worlds, and over 600 other titles on their website. If you love a good book and want to earn free Bitcoin, consider trying it out.

Certain cryptocurrency blogs, news outlets, and forums will pay you in bitcoin to contribute your insights and write for them, if you have a lot of knowledge about the industry.

You can find article writing gigs for crypto blogs and news outlets on job boards like Coinality.

Popular cryptocurrency forums, like Bitcointalk, offer monetization opportunities to their established members -- companies can advertise their product or service in the signature of their posts.

Because advertisers usually want to partner with top-ranked members, and since the forum increases its members rank based off their activity, Bitcointalk makes it nearly impossible for them to spam their way up from the lowest rank of Newbie to the highest rank of Legendary Member. The only way you can increase your rank and earn free bitcoins is by providing a high quantity of high quality posts.

Bitcointalk lists all bitcoin signature campaigns and rates in this overview.

Original post:
How to Get Bitcoins: 6 Tried-and-True Methods

Bitcoin Rally Above $9K Stalls as Sellers Push BTC Back to Key Support – Cointelegraph

Posted on May 2, 2020 by admin

Bitcoin (BTC) price briefly broke above $9,000 as bulls appear to be in the process of trying to quietly move the price above the resistance level.

Since Friday trading volume for the top-ranked cryptocurrency on CoinMarketCap had been virtually non-existent as the price traded sideways between $8,750-$8,850 for the majority of the day but the weekend is bound to bring about a stronger directional move.

Crypto market daily price chart. Source: Coin360

As reported by Cointelegraph, the presence of a TD9 on the daily time frame, overbought technical indicators, and decreasing trading volume suggested that Bitcoin price had become overextended and traders believed that the loss of momentum would culminate as a retest of underlying support levels.

Although the TD Sequential has proven to be a fairly reliable indicator of trend changes in Bitcoin price action, the digital asset is known for its tendency to push higher even when indicators like the Stoch RSI and MACD are strongly overbought.

Given that the halving is a mere 9 days away, excited investors could simply be overlooking any bearish signals with the belief that the price will continue higher into the halving.

The move to $9,000 occurred on gradually increasing purchasing volume and a bull cross on the moving average convergence divergence. The MACD histogram has flipped positive as momentum continues above the 0 line but the relative strength index has dropped below 50 on the 1-hour timeframe.

BTC USDT 1-hour chart. Source: TradingView

While the move above $9K is encouraging, it lacks strength and the Chaikin Money Flow oscillator remains below 0, and even though there is an hourly pattern of higher lows the tight candlesticks slightly longer upper shadows show momentum and volume remain weak compared to the rally which occurred earlier this week.

As shown by the volume profile visible range indicator on the 1-hr and 4-hr time frame, Bitcoin price needs to hold above $8,950 as this resistance here has prevented the asset from moving higher for the past 2 days.

BTC USDT weekly chart. Source: TradingView

According to Cointelegraph contributor, Micheal van de Poppe, this weeks 35%+ rally ended right at a key resistance block located at $9,200-$9,500. Van de Poppe explained that:

This whole resistance zone provided support throughout the summer of 2019.

For the short term, traders should keep a close eye on hourly volume and whether or not the price can hold above $8,800. If $8,800 is lost, traders will look for the price to retest recent lows at $8,400 and $7,800.

Here is the original post:
Bitcoin Rally Above $9K Stalls as Sellers Push BTC Back to Key Support - Cointelegraph

« First «...10 20 30...1,146 1,1471,1481,149 1,150...1,160 1,170 1,180...»Last »