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Australia’s Archer and its plan for quantum world domination – ZDNet

Archer CEO Dr Mohammad Choucair and quantum technology manager Dr Martin Fuechsle

Quantum computing will revolutionise the world; its potential is so immeasurable that the greatest minds in Redmond, Armonk, and Silicon Valley are spending big on quantum development. But a company by the name of Archer Materials wants to put Sydney, Australia, on the map alongside, if not ahead, of these tech giants.

Universal quantum computers leverage the quantum mechanical phenomena of superposition and entanglement to create states that scale exponentially with the number of quantum bits (qubits).

Here's an explanation: What is quantum computing? Understanding the how, why and when of quantum computers

"Quantum computing represents the next generation of powerful computing, you don't really have to know how your phone works on the inside, you just want it to do things that you couldn't do before," Archer CEO Dr Mohammad Choucair told ZDNet.

"And with quantum computing, you can do things that you couldn't necessarily do before."

There is currently a very small set number of tasks that a quantum computer can do, but Choucair is hopeful that in the future this will grow to be a little bit more consumer-based and business-faced.

Right now, however, quantum computing, for all intents and purposes, is at a very early stage. It's not going to completely displace a classical computer, but it will give the capacity to do more with what we currently have. Choucair believes this will positively impact a range of sectors that are reliant on an increasing amount of computational power.

"This comes to light when you start to want to optimise very large portfolios, or perform a whole bunch of data crunching, AI and all sorts of buzzwords -- but ultimately, you're looking for more computational power. And you can genuinely get speed-ups in computational power based on certain algorithms for certain problems that are currently being identified," he explained.

"The problems that quantum computers can solve are currently being identified and the end users are being engaged."

Archer describes itself as a materials technology company. Its proposition is simple at heart: "Materials are the tangible physical basis of all technology. We're developing and integrating materials to address complex global challenges in quantum technology, human health, and reliable energy".

There are many components to quantum computing, but Archer is building a qubit processor. 12CQ is touted by the company as a "world-first technology that Archer aims to build for quantum computing operation at room-temperature and integration onboard modern electronic devices".

"We're not building the entire computer, we're building the chipset, the processer at the core of it," Choucair told ZDNet. "That really forms the brain of a quantum computer.

"The difference with us is that we really are looking at on-board use, rather than the heavy infrastructure that's required to house the existing quantum computing architectures.

"This is not all airy-fairy and it is not all of blue sky; it's real, there's proven potential, we've published the workwe have the data, we have the science behind us -- it took seven years of immense, immersive R&D."

Archer is building the chip inside a AU$180 million prototype foundry out of the University of Sydney. The funding was provided by the university as well as government.

"Everyone's playing their role to get this to market," he said.

Choucair is convinced that the potential when Archer "gets this right" will be phenomenal.

"Once you get a minimal viable product, and you can demonstrate the technology can indeed work at room temperature and be integrated into modern-day electronics. I think that's, that's quite disruptive. And it's quite exciting," he said.

Magnified region observing the round qubit clusters which are billionths of a meter in size in the centre of qubit control device components (appearing as parallel lines).

Choucair found himself at Archer in 2017 after the company acquired a startup he founded. Straight away, he and the board got started on the strategy it's currently executing on.

"There is very, very small margin for error from the start, in the middle, at the end -- you need to know what you're getting yourself into, what you're doingthis is why I think we've been able to be so successful moving forward, we've been so rapid in our development, because we know exactly what needs to get done," Choucair said.

"The chip is a world firstscience can fail at any stage, everybody knows that, but more often than not, it may or may not -- how uncertain do you want something to be? So for us, the more and more we develop our chip, the higher chances of success become."

Read more about Archer's commercial strategy here: Archer looks to commercialisation future with graphene-based biosensor tech

Choucair said materials technology itself was able to reduce a lot of the commercial barriers to entry for Archer, which meant the company could take the work out of the university much sooner.

"The material technology allowed us to do things without the need for heavy cooling infrastructure, which costs millions and millions of dollars and had to be housed in buildings that cost millions and millions of dollars,' he explained. "Massive barrier reduced, material could be made simply from common laboratory agents, which means you didn't have to build a billion-dollar facility to control atoms and do all these crazy scientific things at the atomic level.

"And so, really, you end up with the materials technology that was simple to handle, easy to make, and worked at room temperature, and you're like, wow, okay, so now the job for us is to actually build the chip and miniaturise this stuff, which is challenging in itself."

The CEO of the unexplainable has an impressive resum. He landed at Archer with a strong technical background in nanotechnology, served a two-year mandate on the World Economic Forum Global Council for Advanced Materials, is a fellow of both The Royal Society of New South Wales and The Royal Australian Chemical Institute, and was an academic and research fellow at the University of Sydney's School of Chemistry.

Choucair also has in his armoury Dr Martin Fuechsle, who is recognised for developing the world's smallest transistor, a "single-atom transistor".

"Fuechsle is among the few highly talented physicists in the world capable of building quantum devices that push the boundaries of current information processing technology," Choucair said in January 2019, announcing Fuechsle's appointment. "His skills, experience, and exceptional track record strongly align to Archer's requirements for developing our key vertical of quantum technology."

SEE:Guide to Becoming a Digital Transformation Champion(TechRepublic Premium)

Archer is publicly listed on the Australian Securities Exchange, but Choucair would reject any claims of it being a crazy proposition.

"20 years ago, a company that was maybe offering something as abstract as an online financial payment system would have been insane too, but if you have a look at the top 10 companies on the Nasdaqa lot of their core business is embedded in the development of computational architecture, computational hardware," he said.

"We're a very small company, I'm not comparing myself to a Nasdaq-listed company. I'm just saying, the core businessI think it's a unique offering and differentiates us on a stock exchange."

He said quantum technology is something that people are starting to value and see as having potential and scale of opportunity.

Unlike many of the other quantum players in Australia and abroad, Archer is not a result of a spin-off from a university, Choucair claimed.

"The one thing about Archer is that we're not a university spin out -- I think that's what sets us apart, not just in Australia, but globally," he said. "A lot of the time, the quantum is at a university, this is where you go to learn about quantum computing, so it's only natural that it does come out of a university."

Historically, Australia has a reputation of being bad at commercialising research and development. But our curriculum vitae speaks for itself: Spray-on skin, the black box flight recorder, polymer bank notes, and the Cochlear implant, to name a few.

According to Choucair, quantum is next.

"We really are leading the world; we well and truly punch above our weight when it comes to the work that's been done, we lead the world," he said.

"And that quantum technology is across quantum computing and photonics, and sensing -- it's not just quantum computing. We do have a lot of great scientists and those who are developing the technology."

But as highlighted in May by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in its quantum technologies roadmap, there are a lot of gaps that need to be filled over the long term.

"We just have to go out there and get the job done," Choucair said.

"In Australia we have resource constraints, just like anywhere else in the world. And I think there's always a lot more that can be donewe're not doing deep tech as a luxury in this country. From the very top down, there is an understanding, I believe, from our government and from key institutes in the nation that this is what will help us drive forward as a nation."

Archer isn't the only group focused on the promise of quantum tech down under, but Choucair said there's no animosity within the Aussie ecosystem.

Read about UNSW's efforts: Australia's ambitious plan to win the quantum race

There's also a partnership between two universities: UNSW and Sydney Uni quantum partnership already bearing fruit

"I think we all understand that there's a greater mission at stake here. And we all want, I can't speak on everyone's behalf, but at Archer we definitely have vision of making quantum computing widespread -- adopted by consumers and businesses, that's something that we really want to do," he said.

"We have fantastic support here in Australia, there's no doubt about it."

A lot of the work in the quantum space is around education, as Choucair said, it's not something that just comes out of abstractness and then just exists.

"You have to remember this stuff's all been built off 20, 30, 40 years of research and development, quantum mechanics, engineering, science, and tech -- hundreds and thousands of brilliant minds over the course of two-three generations," the CEO explained.

While the technology is here, and people are building algorithms that only run on quantum computers, there is still another 20-or-so years of development to follow.

"This field is not a fast follower field, you don't just get up in the morning and put your slippers on and say you're going to build a quantum computer," he added.

Archer is also part of the IBM Q Network, which is a global network of startups, Fortune 500 companies, and academic research institutes that have access to IBM's experts, developer tools, and cloud-based quantum systems through IBM Q Cloud.

Archer joined the network in May as the first Australian company that's developing a qubit processor.

Choucair said the work cannot be done without partnerships and collaboration alongside the best in the world.

"Yes, there is a race to build quantum computers, but I think more broadly than a race, to just enable the widespread adoption of the technology. And that's not easy. And that takes a concerted effort," he said. "And at this early stage of development, there is a lot of overlap and collaboration.

"There's a bit of a subculture that Australia can't do it -- yeah, we can.

"There's no excuses, right? We're doing it, we're building it, we're getting there. We're working with the very best in the world."

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Quantum Computing Expert Warns Governments May Be First to Crack Algorithms Keeping Bitcoin and the Internet Secure – The Daily Hodl

Applied mathematician Peter Shor says government agencies could be the first to figure out a way to enable quantum computers to break algorithms that keep Bitcoin and the internet secure.

In an interview with Nature Magazine, the MIT professor of applied mathematics talks about the looming possibility that quantum computers can crack encryption keys, called RSA, that keep the internet and cryptocurrencies safe from security threats. Shor says that if theres anyone who can break the RSA first, it will be government bodies such as the National Security Agency (NSA).

The first people who break RSA either are going to be NSA or some other big organization. At first, these computers will be slow. If you have a computer that can only break, say, one RSA key per hour, anything thats not a high priority or a national-security risk is not going to be broken. The NSA has much more important things to use their quantum computer on than reading your e-mail theyll be reading the Chinese ambassadors e-mail.

Crypto enthusiasts are keeping close tabs on developments in the quantum computing space as the technology threatens to break the cryptographic algorithms that keep cryptocurrencies like Bitcoin secure. The World Economic Forum describes how quantum computing machines can crack the existing standards of encryption.

The sheer calculating ability of a sufficiently powerful and error-corrected quantum computer means that public-key cryptography is destined to fail, and would put the technology used to protect many of todays fundamental digital systems and activities at risk.

Recently, industrial powerhouse Honeywell announced that it built the System Model H1 quantum computer, which the company touts generates the highest quantum volume in the entire industry.

As to whether quantum computing poses an existential threat to the crypto industry, Ripple CTO David Schwartz says it could become powerful enough to break cryptographic algorithms within a decade.

I think we have at least eight years. I have very high confidence that its at least a decade before quantum computing presents a threat, but you never know when there could be a breakthrough. Im a cautious and concerned observer, I would say.

Featured Image: Shutterstock/archy13

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Will Quantum Mechanics Produce the True Thinking Computer? – Walter Bradley Center for Natural and Artificial Intelligence

Some hope that quantum mechanics can explain human consciousness.

Maybe we are all quantum computers but dont know it? Maybe quantum computers could think like people?

There is an odd relationship between the human mind and quantum mechanics, the science of entities like electrons that are too small to be governed by ordinary physics.

Some aspects of consciousness appear to be mediated by such elementary particles. Science writer Philip Ball explains,

Nobody understands what consciousness is or how it works. Nobody understands quantum mechanics either. Could that be more than coincidence?

Quantum mechanics is the best theory we have for describing the world at the nuts-and-bolts level of atoms and subatomic particles. Perhaps the most renowned of its mysteries is the fact that the outcome of a quantum experiment can change depending on whether or not we choose to measure some property of the particles involved

To this day, physicists do not agree on the best way to interpret these quantum experiments, and to some extent what you make of them is (at the moment) up to you. But one way or another, it is hard to avoid the implication that consciousness and quantum mechanics are somehow linked.

This might, of course, be at least one part of the reason that consciousness remains a mystery.

But now, is a quantum computer smarter than the conventional machine that just computes numbers?

In Gaming AI, tech philosopher George Gilder notes that the resourceful AI geniuses believe that they can effect an astronomical speedup by changing the ordinary 1 or 0 bit to the quantum bit, or qubit:

The qubit is one of the most enigmatic tangles of matter and ghost in the entire armament of physics. Like a binary digit, it can register 0 or 1; what makes it quantum is that it can also register a nonbinary superposition of 0 and 1.

But before we get carried away by the possibilities, Gilder goes on to say that theres a hitch. An endless superposition works fine for Schrodingers cat. But, to be useful in the real world, the quantum computer must settle on either 0 or 1. If the needed number is your paycheck, to be cashed, it must be a number, not an infinite debate.

In any event, quantum computers come with real world problems that conventional computers dont have:

the chip can no longer function as a determinist logical device. For example, today the key problem in microchips is to avoid spontaneous quantum tunneling, where electrons can find themselves on the other side of a barrier that by the laws of classical physics would have been insurmountable and impenetrable. In digital memory chips or processors, spontaneous tunneling can mean leakage and loss.

Quantum computing has advantages and disadvantages. In any event, consciousness is still a mystery and its not clear at this point how quantum computers help us understand much. But stay tuned!

Note: You can download Gaming AI for free here.

You may also wish to look at:

Quantum supremacy isnt the Big Fix. If human thought is Turings halting oracle, as seems likely, then even quantum computing will not allow us to replicate human intelligence (Eric Holloway)

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Will Quantum Mechanics Produce the True Thinking Computer? - Walter Bradley Center for Natural and Artificial Intelligence

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Strategic Partnership will aid smooth work in the event of regional crisis: Australia High Commissioner – The Hindu

Artificial Intelligence, 5G, rare earth products, ground station tracking facilities to support Gaganyaan are among the areas covered, says Barry OFarell

Australian High Commissioner to India Barry OFarrell took charge a month before the COVID-19 pandemic struck in India, yet his time here has seen a steady uptick in the momentum of bilateral cooperation including a Prime Ministerial summit in June and, more recently, Australias inclusion in the Malabar naval exercises. He speaks toNarayan Lakshman about a range of cooperative initiatives on the anvil.

It will demonstrate the ability of our navy to work through exercises, warfare serials and like with the navies of India, Australia, the U.S. and Japan. That is important because, were there to be a regional crisis, like a natural or humanitarian disaster, the ability to work smoothly with partners is critical. It builds particularly on the maritime agreement that was one of the agreements underneath the CSP, but also to the mutual logistic support arrangement, which is designed to improve the collaboration between our armed forces. This reflects the commitment that Quad partners have to a free, open, and prosperous Indo Pacific. It demonstrates the commitment that Australia and India have to what Prime Minister Modi described at the June summit as a sacred duty to provide the neighbourhood with the environment where people could prosper, where there could be stability upon which to build your lives, and where you could live freely. It reiterates that.

It also comes off the back of ongoing interactions between our armed forces. To some extent, Malabar was a fixation that we are delighted to be part of, but it was a fixation because it ignored the fact that the AusIndex exercise last year was the largest naval engagement Australia had ever been a part of, and most complex involving submarine serials and P-8 Poseidon maritime patrols across the Bay of Bengal. Equally, the recent passage exercise again demonstrated our ability to work together, including practising warfare serials on water. All these things increase the level of cooperation, increase the significance of the relationship, but practically ensure that should they be called upon, our navies could work more closely together, effectively, in support of a peaceful, stable and prosperous Indo Pacific.

Also read: India-Australia friendship based on trust, respect: Scott Morrison

Certainly, the COVID-19 pandemic has damaged economies. It has accelerated geostrategic competition, and it has obviously disrupted our way of life. It has highlighted the importance, to countries like India and Australia, of ensuring a safe, secure and prosperous future for our citizens. Thats why, as part of the CSP, there were agreements in relation to critical technologies such as Artificial Intelligence, quantum computing and 5G because we recognise the opportunities they present to people, to businesses, to the broader economy, and the fact that they should be guarded by international standards to ensure they do not present risks, to security or prosperity. The Australia-India framework Arrangements on Cyber and Cyber Enabled Critical Technology cooperation, abbreviated as the Arrangement, will enhance bilateral cooperation. Under the agreement, we are going to cooperate together to promote and preserve that open, free, safe and secure Internet by working around those international norms and rules that we talk about. It sets out practical ways to promote and enhance digital trade, harness critical technologies, and address cyber security challenges. It provides a programme of 66 crore over four years for an Australia-India cyber and critical technology partnership to support research by institutions in both Australia and between institutions in Australia and India. We also signed an MoU on critical minerals between both countries because they are the essential inputs into these critical and emerging technologies, which cover areas like high tech electronics, telecommunications, clean energy, transport and defence. Critical minerals are essential if India wants to achieve its energy mission goal in the battery industry, storage industry and electric vehicle industry.

Editorial | A new dimension: On India-U.S.-Australia-Japan Quadrilateral

If you want to build batteries or electric vehicles, lithium, amongst other items, is required. We know that your northern neighbour is your most significant supplier of these critical minerals. We know that India is seeking to become more self-reliant. We know that imports from China are reducing. Australia potentially sees an opportunity for us to provide elements into Indias efforts to improve its manufacturing, defence and electric vehicle and energy mission projects. We have Indian companies who are currently owning or significant investors in Australian critical minerals and rare earths companies. We have just released a new prospectus on critical minerals and rare earths which lists over 200 projects capable of attracting more investment into India.

I know theres concern in some parts of the community that self-reliance means protectionism. Well, we believe, firstly, that that is not the case, and that there will always be markets in India for elements that can be used by India to grow economies, grow businesses and provide more jobs and more wealth into society. But secondly, if you were concerned about the protectionist angle, the fact is that there is nothing stopping you coming to Australia to buy a mine to put those resources, those elements, into your own businesses, in the same way as is happening with coalfield in Queensland.

Also read: Malabar 2020: the coming together of the Quad in the seas

Firstly, Australia is already contributing to Indias national quantum mission by facilitating partnerships with universities, research institutions and businesses. That includes one of the best relationships we have with India, which is the Australian India Strategic Research Fund, which has been going for over 20 years. Since 2013, one of our Australians of the Year, Professor Michelle Simmons, has led a team of researchers at New South Wales Universitys (UNSW) Centre for Quantum Computation and Communication Technology, seeking to build the first quantum computer in silicon.

For quantum computers to be successful with their calculations, they have to be 100% accurate, but electrical interference called charge noise gets in the way. To tackle this problem, the UNSW has used a Research Fund from that Australia India Strategic Research Fund to collaborate with the Indian Institute of Science Bangalore, to combine Australias state of the art fabrication facilities, and Indias ultra-sensitive noise measurement apparatus. This has helped identify how and where the fabrication process should be adjusted. Earlier this year, the UNSW team was able to achieve a 99.99% accuracy in their atomic level silicon prototype. They believe it is only a matter of time before theyre able to demonstrate 100% reliability, and produce a 10 qubit prototype quantum integrated processor, hopefully by 2023. This has the potential to revolutionise virtually every industry, solving problems and processing information that would take a conventional computer millions of years to calculate in seconds. This is practical cooperation between the UNSW and the Institute in Bangalore, going on right now ready to hopefully come to practical fruition in 2023. Equally, in the upcoming Bengaluru Tech Summit we will host an exclusive session providing an overview of our innovative ecosystem, our cyber and critical technology capabilities, growing space ambitions, and the applications of computing, and quantum computing. Professor Simmons will be one of the keynote speakers. We recommend tuning into 11 a.m. on Friday November 20 for the session From Cyberspace to Outer Space: Innovating with Australia in a Post-COVID World. The bottom line is that India and Australia, through two respected institutions, are close to cracking something nowhere else in the world has been cracked, and it is likely to be ready within the next three years.

Firstly, we have a space sector going back to back to 1967. We launched our first rocket in South Australia and Woomera in 1967. But we were also critical to NASA throughout, regarding the use of space as part of NASAs global space infrastructure. We received those pictures from the first moon landing and broadcast them to the world. The U.S.s two systems failed and ours didnt fail on camera, and thats why we had pictures of Neil Armstrong walking on the moon. We have facilitated communication with deep space probes and also the landing craft on Mars.

Australia and India have been cooperating together as countries since 1987, when we inked our first MoU, and there is a strong engagement between ISRO and Australian agencies. We have undertaken data collaboration on Indian remote satellites. Since 2013, we have been doing laser ranging for Indian regional navigational satellite systems. We launched an Australian satellite by an Australian company and of course, we look forward to your manned space mission in 2022. We are exploring how we can place temporary ground station tracking facilities in Australia to support that Gaganyaan Mission. That is something that is practically under way as we speak. But we have been impressed by Indias capabilities and ambitions in space. You have the record for the most number of satellites released by a single rocket ever. It was more than 100 in 2017.

A lot of the universities are using the online option. As someone whos been coming to India for 10 years, initially I did notice a resistance to online education. Like the other technologies that were finally using during COVID, that resistance has been broken down. I confirmed that with the Director of the Indian Institute of Technology, IIT Madras. But we recognise that it is face-to-face learning, like face-to-face working, is still what most people want. A number of Australian States are starting pilot programmes to demonstrate that students can be picked up and returned to Australia into campuses safely given the COVID spread. And my Education Minister Dan Tehan made the point two weeks ago that the Australian government is keen for that to happen as soon as possible. The latest part to be announced was one from South Australia that will fly students out of Singapore into Australia. There was an early one announced by the Northern Territory. On the back of those, there is a hope that we will be able to return students to Australia for Day One, Term One, next year. But it will depend on those State trials. It is a bit like our approach to opening up bubbles with other countries: we would like to see things being done in situ, in practice, in real time to show that it can succeed. If the trials are successful, I remain confident about next year.

The challenge at the present time is that both countries have international flight bans. The only flights operating between both countries are repatriation flights. Malaysia and Singapore, which were the two countries in pre-COVID times where passengers could transit to get to Australia or to come to India, are not accepting Indian citizens. But that in no way undermines Australias desire to resume whatever is going to be business as usual, in relation to tertiary education.

Australian State governments and our education institutions themselves have put a lot of effort into looking after those Indian students who were stranded in Australia due to the COVID-19 crisis. Some of them are people that have had to wait a month or two until the Vande Bharat planes started. Having graduated mid-year, they have now hopefully most of them flying home, while others are still continuing their studies. Whilst, like many places at the start of COVID-19, there were a few teething problems, Im delighted to say a combination of State and federal governments and the universities and the Indian community there have been supportive of Indian students in Australia.

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Strategic Partnership will aid smooth work in the event of regional crisis: Australia High Commissioner - The Hindu

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Microsoft Introduces Lobe: A Free Machine Learning Application That Allows You To Create AI Models Without Coding – MarkTechPost

Microsoft has releasedLobe, a free desktop application that lets Windows and Mac users create customized AI models without writing any code. Several customers are already using the app for tracking tourist activity around coral reefs, the company said.

Lobeis available on Windows and Mac as a desktop app. Presently it only supports image classification by categorizing the image to a single label overall. Microsoft says that there will be new releases supporting other neural networks in the near future.

To create an AI in Lobe, a user first needs to import a collection of images. These images are used as a dataset to train the application. Lobe analyzes the input images and sifts through a built-in library of neural network architectures to find the most suitable model for processing the dataset. Then it trains the model on the provided data, creating an AI model optimized to scan images for the users specific object or action.

AutoML is a technology that can automate parts and most of the machine learning creation workflow, reducing the advancement costs. Microsoft has made AutoML features available to enterprises in its Azure public cloud. The existing AI tools in Azure target only advanced projects. Lobe being free, easy to access, and convenient to use can now support even simple use cases that were not adequately addressed by the existing AI tools.

The Nature Conservancy is a nonprofit environmental organization that used Lobe to create an AI. This model analyzes the pictures taken by tourists in the Caribbean to identify where and when visitors interact with coral reefs. A Seattle auto marketing firm,Sincro LLC,has developed an AI model that scans vehicle images in online ads to filter out pictures that are less appealing to the customers.

GitHub: https://github.com/lobe

Website: https://lobe.ai/

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Machine learning and predictive analytics work better together – TechTarget

Like many AI technologies, the difference between machine learning and predictive analytics lies in applications and use cases. Machine learning's ability to learn from previous data sets and stay nimble lends itself to diverse applications like neural networks or image detection, while predictive analytics' narrow focus is on forecasting specific target variables.

Instead of implementing one type of AI or choosing between the two strategies, companies that want to get the most out of their data should combine the processing power of predictive analytics and machine learning.

Artificial intelligence is the replication of human intelligence by machines. This includes numerous technologies such as robotic process automation (RPA), natural language processing (NLP) and machine learning. These diverse technologies each replicate human abilities but often operate differently in order to accomplish their specific tasks.

Machine learning is a form of AI that allows software applications to become progressively more accurate at prediction without being expressly programmed to do so. The algorithms applied to machine learning programs and software are created to be versatile and allow for developers to make changes via hyperparameter tuning. The machine 'learns' by processing large amounts of data and detecting patterns within this set. Machine learning is the foundational basis for advanced technologies like deep learning, neural networks and autonomous vehicle operation.

Machine learning can increase the speed at which data is processed and analyzed and is a clear candidate through which AI and predictive analytics can coalesce. Using machine learning, algorithms can train on even larger data sets and perform deeper analysis on multiple variables with minor changes in deployment.

Machine learning and AI have become enterprise staples, and the debate over value is obsolete in the eyes of Gartner analyst Whit Andrews. In years prior, operationalizing machine learning required a difficult transition for organizations, but the technology has now successful implementation in numerous industries due to the popularity of open source and private software machine learning development.

"Machine learning is easier to use now by far than it was five years ago," Andrews said. "And it's also likely to be more familiar to the organization's business leaders."

As a form of advanced analytics, predictive analytics uses new and historical data in order to predict and forecast behaviors and trends.

Software applications of predictive analytics use variables that can be analyzed to predict the future likely behavior, whether for individual consumers, machinery or sales trends. This form of analytics typically requires expertise in statistical methods and is therefore commonly the domain of data scientists, data analysts and statisticians -- but also requires major oversight in order to function.

For Gartner analyst Andrew White, the crucial piece of deploying predictive analytics is strong business leadership. In order to see successful implementation, enterprises need to be using predictive analytics and data to constantly try and improve business processes. The decisions and outcomes need to be based on the data analytics, which requires a hands-on data science team.

Because of the smaller training samples used to create a specific model that does not have much capacity for learning, White stressed the importance of quality training data. Predictive models and the data they are using need to be equally fine-tuned; confusing the analytics or the data as the main player is a mistake in White's eyes.

"The reality is [data and analytical models] are equal," White said. "You need to have ownership or leadership around prioritizing and governing data as much as you have the same for analytics, because analytics is just the last mile."

Data-rich enterprises have established successful applications for both machine learning and predictive analytics.

Retailers are one of the most predominant enterprises using predictive analytics tools in order to spot website user trends and hyperpersonalize ads and target emails. Massive amounts of data collected from points of sale, retail apps, social media, in-store sensors and voluntary email lists provide insights on sales forecasting, customer experience management, inventory and supply chain.

Another popular application of predictive analytics is predictive maintenance. Manufacturers use predictive analytics to monitor their equipment and machinery and predict when they need to replace or repair valuable pieces.

Predictive analytics is also popularly deployed in risk management, fraud and security, and healthcare applications across enterprises.

Machine learning, on the other hand, has a wider variety of applications, from customer relationship management to self-driving cars. These algorithms are in human resource information systems to identify candidates, within software sold by business intelligence and analytics vendors, as well as in customer relationship management systems.

In businesses, the most popular machine learning applications include chatbots, recommendation engines, market research and image recognition.

Enterprise trend applications are where predictive analytics and AI can converge. Maintaining best data practices as well as focusing on combining the powers of machine learning and predictive analytics is the only way for organizations to keep themselves at the cutting edge of predictive forecasting.

Machine learning algorithms can produce more accurate predictions, create cleaner data and empower predictive analytics to work faster and provide more insight with less oversight. Having a strong predictive analysis model and clean data fuels the machine learning application. While a combination does not necessarily provide more applications, it does mean that the application can be trusted more. Splitting hairs between the two shows that these terms are actually hierarchical and that when combined, they complete one another to strengthen the enterprise.

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Amwell CMO: Google partnership will focus on AI, machine learning to expand into new markets – FierceHealthcare

Amwell is looking to evolve virtual care beyond just imitating in-person care.

To do that, the telehealth companyexpects to use its latestpartnership with Google Cloud toenable it to tap into artificial intelligence and machine learning technologies to create a better healthcare experience, according to Peter Antall, M.D., Amwell's chief medical officer.

"We have a shared vision to advance universal access to care thats cost-effective. We have a shared vision to expand beyond our borders to look at other markets. Ultimately, its a strategic technology collaboration that were most interested in," Antall said of the company's partnership with the tech giant during a STATvirtual event Tuesday.

"What we bring to the table is that we can help provide applications for those technologiesthat will have meaningful effects on consumers and providers," he said.

The use of AI and machine learning can improve bot-based interactions or decision support for providers, he said. The two companies also want to explore the use of natural language processing and automated translation to provide more "value to clients and consumers," he said.

Joining a rush of healthcare technology IPOs in 2020, Amwell went public in August, raising$742 million. Google Cloud and Amwell also announced amultiyear strategic partnership aimed at expanding access to virtual care, accompanied by a$100 million investmentfrom Google.

During an HLTH virtual event earlier this month, Google Cloud director of healthcare solutions Aashima Gupta said cloud and artificial intelligence will "revolutionize telemedicine as we know it."

RELATED:Amwell files to go public with $100M boost from Google

"There's a collective realization in the industry that the future will not look like the past," said Gupta during the HTLH panel.

During the STAT event, Antall said Amwellis putting a big focus onvirtual primary care, which has become an area of interest for health plans and employers.

"It seems to be the next big frontier. Weve been working on it for three years, and were very excited. So much of healthcare is ongoing chronic conditions and so much of the healthcare spend is taking care ofchronic conditionsandtaking care of those conditions in the right care setting and not in the emergency department," he said.

The companyworks with 55 health plans, which support over 36,000 employers and collectively represent more than 80million covered lives, as well as 150 of the nations largest health systems. To date, Amwell says it has powered over 5.6million telehealth visits for its clients, including more than 2.9million in the six months ended June 30, 2020.

Amwell is interested in interacting with patients beyond telehealth visits through what Antall called "nudges" and synchronous communication to encouragecompliance with healthy behaviors, he said.

RELATED:Amwell CEOs on the telehealth boom and why it will 'democratize' healthcare

It's an area where Livongo, recently acquired by Amwell competitor Teladoc,has become the category leader by using digital health tools to help with chronic condition management.

"Were moving into similar areas, but doing it in a slightly different matter interms of how we address ongoing continuity of care and how we address certain disease states and overall wellness," Antallsaid, in reference to Livongo's capabilities.

The telehealth company also wants to expand into home healthcare through the integration of telehealth and remote care devices.

Virtual care companies have been actively pursuing deals to build out their service and product lines as the use of telehealth soars. To this end, Amwell recently deepened its relationship with remote device company Tyto Care. Through the partnership, the TytoHome handheld examination device that allows patients to exam their heart, lungs, skin, ears, abdomen, and throat at home, is nowpaired withAmwells telehealth platform.

Looking forward, there is the potential for patients to getlab testing, diagnostic testing, and virtual visits with physicians all at home, Antall said.

"I think were going to see a real revolution in terms ofhow much more we can do in the home going forward," he said.

RELATED:Amwell's stock jumps on speculation of potential UnitedHealth deal: media report

Amwell also is exploring the use of televisions in the home to interact with patients, he said.

"We've done work with some partners and we're working toward a future where, if it's easier for you to click your remote and initiate a telehealth visit that way, thats one option. In some populations, particularly the elderly, a TV could serve as a remote patient device where a doctor or nurse could proactively 'ring the doorbell' on the TV and askto check on the patient," Antall said.

"Its video technology that'salready there in most homes, you just need a camera to go with it and a little bit of software.Its one part of our strategy to be available for the whole spectrum of care and be able to interact in a variety of ways," he said.

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Amwell CMO: Google partnership will focus on AI, machine learning to expand into new markets - FierceHealthcare

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93% of security operations centers employing AI and machine learning tools to detect advanced threats – Security Magazine

93% of security operations center employing AI and machine learning tools to detect advanced threats | 2020-10-30 | Security Magazine This website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more. This Website Uses CookiesBy closing this message or continuing to use our site, you agree to our cookie policy. Learn MoreThis website requires certain cookies to work and uses other cookies to help you have the best experience. By visiting this website, certain cookies have already been set, which you may delete and block. By closing this message or continuing to use our site, you agree to the use of cookies. Visit our updated privacy and cookie policy to learn more.

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93% of security operations centers employing AI and machine learning tools to detect advanced threats - Security Magazine

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Microsoft/MITRE group declares war on machine learning vulnerabilities with Adversarial ML Threat Matrix – Diginomica

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The extraordinary advances in machine learning that drive the increasing accuracy and reliability of artificial intelligence systems have been matched by a corresponding growth in malicious attacks by bad actors seeking to exploit a new breed of vulnerabilities designed to distort the results.

Microsoft reports it has seen a notable increase in attacks on commercial ML systems over the past four years. Other reports have also brought attention to this problem.Gartner's Top 10 Strategic Technology Trends for 2020, published in October 2019, predicts that:

Through 2022, 30% of all AI cyberattacks will leverage training-data poisoning, AI model theft, or adversarial samples to attack AI-powered systems.

Training data poisoning happens when an adversary is able to introduce bad data into your model's training pool, and hence get it to learn things that are wrong. One approach is to target your ML's availability; the other targets its integrity (commonly known as "backdoor" attacks). Availability attacks aim to inject so much bad data into your system that whatever boundaries your model learns are basically worthless. Integrity attacks are more insidious because the developer isn't aware of them so attackers can sneak in and get the system to do what they want.

Model theft techniques are used to recover models or information about data used during training which is a major concern because AI models represent valuable intellectual property trained on potentially sensitive data including financial trades, medical records, or user transactions.The aim of adversaries is to recreate AI models by utilizing the public API and refining their own model using it as a guide.

Adversarial examples are inputs to machine learning models that attackers haveintentionally designed to cause the model to make a mistake.Basically, they are like optical illusions for machines.

All of these methods are dangerous and growing in both volume and sophistication. As Ann Johnson Corporate Vice President, SCI Business Development at Microsoft wrote in ablog post:

Despite the compelling reasons to secure ML systems, Microsoft's survey spanning 28 businesses found that most industry practitioners have yet to come to terms with adversarial machine learning. Twenty-five out of the 28 businesses indicated that they don't have the right tools in place to secure their ML systems. What's more, they are explicitly looking for guidance. We found that preparation is not just limited to smaller organizations. We spoke to Fortune 500 companies, governments, non-profits, and small and mid-sized organizations.

Responding to the growing threat, last week, Microsoft, the nonprofit MITRE Corporation, and 11 organizations including IBM, Nvidia, Airbus, and Bosch released theAdversarial ML Threat Matrix, an industry-focused open framework designed to help security analysts to detect, respond to, and remediate threats against machine learning systems. Microsoft says it worked with MITRE to build a schema that organizes the approaches employed by malicious actors in subverting machine learning models, bolstering monitoring strategies around organizations' mission-critical systems.Said Johnson:

Microsoft worked with MITRE to create the Adversarial ML Threat Matrix, because we believe the first step in empowering security teams to defend against attacks on ML systems, is to have a framework that systematically organizes the techniques employed by malicious adversaries in subverting ML systems. We hope that the security community can use the tabulated tactics and techniques to bolster their monitoring strategies around their organization's mission critical ML systems.

The Adversarial ML Threat, modeled after the MITRE ATT&CK Framework, aims to address the problem with a curated set of vulnerabilities and adversary behaviors that Microsoft and MITRE vetted to be effective against production systems. With input from researchers at the University of Toronto, Cardiff University, and the Software Engineering Institute at Carnegie Mellon University, Microsoft and MITRE created a list of tactics that correspond to broad categories of adversary action.

Techniques in the schema fall within one tactic and are illustrated by a series of case studies covering how well-known attacks such as the Microsoft Tay poisoning, the Proofpoint evasion attack, and other attacks could be analyzed using the Threat Matrix. Noted Charles Clancy, MITRE's chief futurist, senior vice president, and general manager of MITRE Labs:

Unlike traditional cybersecurity vulnerabilities that are tied to specific software and hardware systems, adversarial ML vulnerabilities are enabled by inherent limitations underlying ML algorithms. Data can be weaponized in new ways which requires an extension of how we model cyber adversary behavior, to reflect emerging threat vectors and the rapidly evolving adversarial machine learning attack lifecycle.

Mikel Rodriguez, a machine learning researcher at MITRE who also oversees MITRE's Decision Science research programs, said that AI is now at the same stage now where the internet was in the late 1980s when people were focused on getting the technology to work and not thinking that much about longer term implications for security and privacy. That, he says, was a mistake that we can learn from.

The Adversarial ML Threat Matrix will allow security analysts to work with threat models that are grounded in real-world incidents that emulate adversary behavior with machine learning and to develop a common language that allows for better communications and collaboration.

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Leveraging Machine Learning and IDP to Scale Your Automation Program – AiiA

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As document and input types get more and more complex, legacy business process automation technologies, like Robotic Process Automation (RPA), can struggle to keep up. Designed to execute precise rules and work with structured data inputs, these approaches lack the intelligence to handle the variability and ambiguity of diverse, real-world document processing workflows, making it a partial enterprise solution that needs to be supplemented with more intelligent technology.

Fortunately, theres a sea change coming to back offices, reshaping the way organizations operate. Recent breakthroughs in Artificial Intelligence - and Machine Learning, specifically - are helping businesses replace aging tech stacks and inflexible workflows with technology that supports the kind of responsiveness and innovation required to keep pace with an ever-changing market. These advances bring forth a reliable path towards automating processes that have previously only been possible by people, and they finally fulfill the promises made (and broken) by earlier technologies many times before.

Intelligent Document Processing (IDP) solutions, in particular, leverage the latest in ML and AI to capture data from documents (e.g. text, PDFs, scanned images, emails), and categorizes and extracts relevant data for further processing. Leading IDP solutions that leverage the latest in Machine Learning continue to learn on the data theyre exposed to, driving lower error rates and greater automation.

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Leveraging Machine Learning and IDP to Scale Your Automation Program - AiiA

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