The beautiful and culturally progressive State of Qatar is home to the world-class post-secondary institution, College of the North Atlantic-Qatar (CNA-Q). Internationally recognized as a comprehensive technical college, CNA-Q is committed to high quality, student-centered education. This commitment is reflected through state-of-the-art facilities, accessible and responsive technology programs and strong partnerships with industry. CNA-Q will soon be transformed into a National University.

With more than 600 staff and over 5,000 students, CNA-Q is one of Qatars largest post-secondary institutions offering over 50 different level program (Diploma, Bachelor, and Masters), through student-centred learning. By providing training in a range of technical areas including Engineering Technology, Health Sciences, Industrial Trades, Business Studies and Computing & Information Technology, CNA-Q brings the State closer to the goals of Qatar National Vision 2030.

The School of Computing and Information Technology (SCIT) invites applications for positions at the level of Assistant / Associate Professor in Data Science and Artificial Intelligence. The School offers several trendy programs such Bachelor of Applied Science in Data Science and AI (AI & Data Analytics, AI & IoT), Bachelor of Applied Science in Data & Cyber Security (Ethical Hacking, Cyber Defense, Industrial Control Systems Security, Cyber Security Policy and Governance), Bachelor of Applied Science in Information Systems (Software Development, Mobile & Web Development, and Database Design & Administration), and Bachelor of Applied Science in Information Technology (Computer Systems, Network Systems, and Cloud Computing & Big Data).

Duties & Responsibilities:

The primary role of the faculty members at the School of Computing and IT is to promote high-quality innovative teaching, applied research, and services. Besides, he/she should collaborate with the Head of Department, School's Dean, and the colleagues to achieve the department's and School's mission, mentor junior colleagues, and teaching assistants, and support the department and the School with several administrative and academic services.

Reporting to the Department Chair, the successful candidate will be responsible for the development, delivery and evaluation of a broad range of courses within Data Science and Artificial Intelligence. Particular areas of interest include Machine Learning, Deep Learning, Visualization and Intelligent Interaction, Industrial and Business Analytics, IoT Software and System, and IoT Intelligence and Automation, but candidates with strong expertise in other areas of Data Science and Artificial Intelligence will also be considered. Other duties include evaluation of student progress and management of resources of the learning environment.The successful candidate will liaise with industry and other educational institutions; participate in industry advisory committees and coordinate, manage and control projects within the specified program area. Faculty members will keep course portfolio documents required for accreditation processes and engage in instructional development/improvement plans. All employees are expected to contribute to professional and community life within the College and beyond.

Required Qualifications:

For Assistant Professor

A PhD degree in Data Science and Artificial Intelligence or closely related field. Three years teaching experience in a higher-education environment, along with three years of employment experience as a practitioner/professional within a relevant discipline is preferred. Candidates should also be recognized in the following criteria:

For Associate Professor

A PhD degree in Data Science and Artificial Intelligence or closely related field. A minimum of 5 years teaching experience in a higher-education environment is required. Also, 5 years of Industrial experience as a practitioner/professional within a relevant discipline is preferred. Candidates should also be recognized in the following criteria:

Preferred Qualifications:

Other Required Skills:

How to Apply:

Applications should be submitted via our online application portal.

You must meet all essential qualifications in order to be appointed to the position. Other qualifications may be a deciding factor in choosing the person to be appointed. Some essential and other qualifications will be assessed through your application, which may include (but need not be limited to) curricula vitae, cover letters, references, teaching dossiers, and sample publications. It is your responsibility to provide appropriate examples that illustrate how you meet each qualification. Failing to do so could result in your application being rejected.

We thank all those who apply. Only those selected for further consideration will be contacted.

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Assistant/Associate Professor in Data Science / Artificial Intelligence job with COLLEGE OF THE NORTH ATLANTIC- QATAR | 279203 - Times Higher...

DUBLIN--(BUSINESS WIRE)--The "Global Open-Source Intelligence Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Technique (Text Analytics, Video Analytics, Social Media Analytics, Geospatial Analytics, Security Analytics, and Others) and End-User" report has been added to ResearchAndMarkets.com's offering.

The global open-source intelligence market was valued at Euro 3,422.74 million in 2021 and is projected to reach Euro 10,858.24 million by 2028; it is expected to grow at a CAGR of 17.9% from 2021 to 2028.

Over a few years, social media has gained momentum across the world. More than 80% of the global population has at least one social media account. Apart from using social media account for communication, individuals are using it for earning. Social media has also become a marketing platform for both individuals and businesses. Social media networks provide several options for internet investigations because a large amount of important information is available at one location.

For example, any personal information can be obtained from anywhere across the world by checking a person's Facebook profile. The information gathered from social media websites is referred to as social media intelligence (SOCMINT), which is a subbranch of open-source intelligence (OSINT). Social media platforms can have both public posts and private posts. Without the creator's consent, private information-such as materials shared with friend circles-cannot be accessed. However, with the rise in the use of social media, content and data theft have also experienced a surge over the years.

Therefore, the adoption of social media intelligence is increasing across businesses to protect every data published on their social media pages. For instance, MEDUSA offers a platform to analyze digital data from social media, dark web, forums, and closed databases to help organizations fight against serious crimes. Thus, the above-mentioned factors are expected to fuel the growth of the open-source intelligence market in the future.

The global open-source intelligence market is segmented on the basis of technique, end user, and geography. Based on technique, the market is segmented into text analytics, video analytics, social media analytics, geospatial analytics, security analytics, and others. Based on end user, the open-source intelligence market is segmented into government intelligence agencies, military and defense intelligence agencies, cyber security organizations, law enforcement agencies, private specialized business, financial services, and others. Geographically, the market is segmented into North America (the US, Canada, and Mexico), Europe (France, Germany, Italy, the UK, Russia, and the Rest of Europe), Asia Pacific (Australia, China, India, Japan, South Korea, and the Rest of APAC), Middle East & Africa (Saudi Arabia, South Africa, the UAE, and the Rest of MEA), and South America (Brazil, Argentina, and the Rest of SAM).

Reasons to buy

Market Dynamics

Drivers

Restraint

Opportunities

Future Trends

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/pjo203

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Worldwide Open-source Intelligence Industry to 2028 - Integration of Artificial Intelligence with Open-Source Intelligence Presents Opportunities -...

Market.us provides a thorough evaluation of the Artificial Intelligence in Transportation market. It evaluates commercial enterprise solutions and studies, improvement, applications, benefits, advantages, scope and operations. This market research report Artificial Intelligence in Transportation provides an in-depth evaluation and improvement of key producers, challengers, global providers, and risks. This report also provides an aggressive assessment of the state-of-the-art technology, innovation and upcoming scope. It also examines risks and access barriers.

The research also includes the Artificial Intelligence in Transportation markets key achievements, studies & improvements, new product launches, nearby boom, main competition over commonplace and near scale. Enterprise report analysis and insights of Artificial Intelligence in Transportation producers. It includes information about sales, percentages, supply, opportunities, challenges, and barriers to growth. It also allows for the expansion of industry in nearby areas as well as worldwide figures and records. Market.us must also have access to many famous worldwide and local paid databases. This allows them to determine the Artificial Intelligence in Transportation market dynamics and developments. These studies also include key strategic trends such as R&D, product launches, agreements, collaborations Artificial Intelligence in Transportation partnerships, joint ventures and the improvement of fundamental competition within the market.

To use a sample copy of the report, go to @https://market.us/report/artificial-intelligence-in-transportation-market/request-sample/

This Evaluation converges to the best top players in the global Artificial Intelligence in Transportation market:

ContinentalMagnaBoschValeoZFScaniaPaccarVolvoDaimlerNvidiaAlphabetIntelMicrosoft

The Figure Indicated Graphical Representation:

Description of the Report

This report gives key insights into the global market for Artificial Intelligence in Transportation and the key factors that have contributed to its popularity. It also provides an assessment of the long-term as well short-term strategies that are necessary to succeed in this market. The report segments the global market using the basic_segment. The report starts with an executive overview, which covers the definition and creation the market. This section also contains an assessment of the market, based entirely on the supply and demand within the international Artificial Intelligence in Transportation market. An impact analysis using the weighted-average version is provided to assist in making accurate business decisions.

The segments are further broken down into sub-segments, and the regions into countries. The report also provides information on the market size in various regions. The report also includes an evaluation of incremental opportunity and basis points share. Global Artificial Intelligence in Transportation market information includes key developments and the most recent technologies. This research reveals key trends within countries that are important in the market boom. In the report, you will find information on the drivers and the restraints that are affecting the market boom in all key areas.

Ask Our Expert for customization and feasibility @https://market.us/report/artificial-intelligence-in-transportation-market/#inquiry

Understanding Segmentation: Global Artificial Intelligence in Transportation Market

Market segment by Type, the product can be split into:

by OfferingHardwareSoftwareby ProcessData MiningImage RecognitionSignal Recognition

Market segment by Application, the market can be split into:

Semi & Full-AutonomousHMIPlatooning

Regional Assessment:

North America Region (U.S., Canada, Mexico)

Europe Region (Germany, UK, France, Russia, Italy, Rest of Europe)

Asia-Pacific Region (China, Japan, South Korea, India, Southeast Asia, Rest of Asia-Pacific)

South America Region (Brazil, Argentina, Columbia, Rest of South America)

The Middle East & Africa Region (Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Rest of MEA)

Our trusted press-release media partner @https://www.taiwannews.com.tw/en/search?keyword=market.us

Research Methodology

To calculate the Artificial Intelligence in Transportation market size, Market.us took into account sales contribution from Artificial Intelligence in Transportation vendors. This report provides a market forecast to show the impact of all the key factors on the global Artificial Intelligence in Transportation market. The forecast can also help manufacturers identify potential market opportunities.

The report provides a forecast of the value and volume for the entire global market for Artificial Intelligence in Transportation. The report examined the current market size to provide a reliable forecast. The market size indicates how the global Artificial Intelligence in Transportation market will perform in the near future. Analysts have triangulated data based on different trends to determine market characteristics.

The Report Answers Key Questions:

What is the boom potential of the Artificial Intelligence in Transportation market?

What is the expected revenue growth for the Keyword Market?

What are the major factors that drive market revenue growth?

What will the market experience in the next few years?

What regions and segments are expected to hold a significant share of the market during the next period?

Which companies are active in the Artificial Intelligence in Transportation Market?

What are the key outcomes of Porters Five Forces analysis and SWOT analysis?

To learn more about this report@https://market.us/report/artificial-intelligence-in-transportation-market/

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Artificial Intelligence In Transportation Market Things That Will Result In Success To 2031 - Taiwan News

French VFX powerhouse MacGuff, with headquarters in Paris, is using proprietary artificial intelligence tools, in particular Face Engine and Body Engine, in a broad range of VFX projects.

Current projects in the pipeline include Season 2 of Lupin for Netflix, Htel du temps for France Tlvisions, and Christian Carions Une belle course, starring Dany Boon. The studio also used AI tools in ric Rochants political thriller series The Bureau.

Htel du temps is a perfect example of the power of Face Engine since it brings historic figures back to life, such as late actor Jean Gabin and Princess Diana, to be interviewed by hard-hitting French journalist Thierry Ardisson.

MacGuff has an in-house R&D department that has been developing proprietary AI tools by mixing open-source software with proprietary code. The AI developments are being overseen by co-founder and joint director Rodolphe Chabrier and MacGuffs veteran VFX supervisor Martial Vallanchon.

MacGuff recently received a 200,000 euros ($230,000) grant from Frances CNC to expand its AI engine, as part of the CNCs $11.4 million technological modernization scheme launched in 2021, which has provided support for 20 French studios and digital post-production companies.

Our AI tools can make people look younger and older, or even bring people back to life! explains Philippe Sonrier, MacGuffs other co-founder and joint director. We were the first studio to develop these tools in Europe. They deliver new narrative options and the chance to make more complex characters.

Sonrier adds: AI is totally different from the method that we have known for the past 30 years, primarily based on complex and time-consuming synthesis methods [modeling, rigging, motion capture, photoreal rendering]. AI brings elements of reality in effects. Its amazing how it makes the images more natural. For example, you can film the movements of an actor and a dancer and then merge the two. Its going to revolutionize our industry.

MacGuff was founded in Paris in 1986. In mid-2011 it split into two companies. Universal bought the animation department, renamed as Illumination MacGuff, run by Jacques Bled.

Sonrier is also co-president of FranceVFX, the French visual effects vendors association, created in 2017, which represents 12 studios: MacGuff, BUF, Digital District, Mikros Image, Trimaran, Solidanim, The Yard, Autre Chose, Les Androds Associs, Reepost, La Plante Rouge and D-Seed.

FranceVFX is a lobby for VFX interests and also serves as a liaison mechanism between the participating members. It has facilitated joint cooperation on more ambitious VFX projects.

One recent example was Martin Bourboulons historical drama Eiffel, with 560 VFX shots made by Buf, MacGuff and CGEV, for which the overall VFX supervisor was Olivier Cauwet. Major VFX work is also being developed for Bourboulons upcoming The Three Musketeers DArtagnan and The Three Musketeers Milady, a $85 million two-part saga based on Alexandre Dumas masterpiece.

Collaboration on VFX projects between various studios is a new model for France that has been tested successfully in the U.S., Canada and the U.K., explains Sonrier. It permits us to be more secure. If one vendor has a problem with a project, we can help each other out. The position of the VFX supervisor is emerging in France.

MacGuff works on major international projects as well as French films and series. It produced VFX work on Julia Ducournaus 2021 Cannes Palme dOr winner, Titane, including the CGI sequences that created the car baby.

Our culture is inevitably very French, explains Sonrier. We like to be very close to the creative decisions and become involved in each project as soon as possible. Thats part of our DNA. Titane is a good example. Initially the director tried out animatronics solutions but wasnt happy with them. We used CGI to create the car baby. Its something wed previously tried out in 2006 when creating a fetus for the French documentary Lodysse de la Vie by Nils Tavernier.

VFX work is always very risky in both creative and financial terms, says Sonrier. This is particularly true in the French tradition, because of the status of the director as the auteur and supreme decision-maker.

For major international films and series, Sonrier considers that it is easier to lock down the logistics, but sometimes at the cost of becoming more like a factory pipeline. MacGuff has forged a strong relationship with Netflix, which was cemented by its VFX work on its gentleman thief series Lupin. Another major VFX job produced for Netflix was Alexandre Ajas 2021 survival thriller Oxygen, where the VFX work alone was budgeted at over 1 million ($1.14 million).

MacGuff is now working on a major international series, which involves coordination between several VFX studios. It is also working on a major animation project between France, Belgium and Canada, and an ambitious French robot-themed project that will begin lensing in mid-2022.

More international projects are coming to France in the wake of the change introduced in 2020 to Frances Tax Rebate for International Production (TRIP) scheme, which now offers a 40% rebate on all eligible expenses including for live action spends that are not VFX related for international projects whose VFX expenses surpass 2 million ($2.27 million) spent in France.

High-profile projects attracted by this change include Ridley Scotts 14th century period epic The Last Duel, with VFX work done by Mikros Image. Another example is the 16th-century Medici drama Serpent Queen, produced for Starz by Lionsgate Television and 3 Arts Entertainment.

Smaller-scale international projects can apply for other support mechanisms such as the CVS scheme for ambitious visual and sound projects. The CVS scheme was used on the Lithuanian-French production Vesper Seeds, for which the VFX work was shared with Mathematic, Mikros Liege and Excuse My French.

This dystopian pic, set after the collapse of the Earths ecosystem, is the third feature from Lithuanian helmer Kristina Buozyte and French helmer Bruno Samper, who co-directed a short segment for the 2014 American horror anthology ABCs of Death 2.

MacGuff is also producing VFX work for the documentary Corridor of Power, produced by Dror Moreh, having previously worked on other projects produced by him, such as Oscar-nominee The Gatekeepers and The Human Factor, which won the Grand Prix at Fipadoc 2020.

Other recent French productions handled by the studio include Nicolas Girauds Lastronaute, starring Giraud and Mathieu Kassovitz.

MacGuff is a long-time collaborator of French-Argentine helmer Gaspar No and did the VFX work on his latest feature film, Vortex, in terms of stabilization of the frames, rotations, small morphs, retiming and adjustments to the split screen images.

The studio also provides VFX for documentaries, such as La rafle des notables, produced by Victor Roberts 10.7 Productions, based on Anne Sinclairs book about French concentration camps during World War II. It is also working on a docufiction from 10.7 Productions The Last Secrets of Humanity, directed by Jacques Malaterre, about the prehistoric period in China, including VFX work to recreate prehistoric animals, jointly produced by Mikros and MacGuff.

The company is developing VR/AR and immersive projects, primarily commercials, via its subsidiary Small.

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MacGuffs Philippe Sonrier on How Artificial Intelligence Tools Will Revolutionize the VFX Industry - Variety

Core music-making skills dont have a shelf life if you could write, record and produce a great track in the past, those abilities are just as valid now as they ever were. Much like riding the proverbial bike.

Those skills might still need a little updating though. Music technology both in terms of how we make it, and how we listen is changing all the time, and its always worth keeping up with the latest developments.

When we talk about intelligent or smart plugins, were generally using these as catch-all terms for a variety of technologies involving some combination of forensic audio analysis, artificial intelligence and machine learning.

These are all terms that crop up in plugin promotional materials with increasing regularity. Their proliferation is down to more than fashion though these are technologies that make use of the increasing processing power of modern computers. They are processes that simply wouldnt have been feasible on home computers in the past.

Broadly speaking, these kinds of plugins are ones that can respond to context. Take an EQ as an example. Although a traditional EQ will let users boost or cut a variety of frequencies and may come stocked with presets aimed at specific types of material, the effect itself pays no heed to the material coming into the input it simply applies a process as instructed.

An intelligent EQ, on the other hand, will listen to the incoming audio and adapt its processes based on what it thinks necessary, such as boosting the top end on a vocal or adding punch to a kick.

These technologies all come down to training algorithms to find patterns. Machine learning involves, essentially, educating a plugin to recognise things so that it can make decisions on how to respond.

At their best, AI-powered plugins tend to support the creative decisions of the music maker, rather than attempt to overrule them

Take a noise reduction tool like those in iZotopes RX, for example. Its ability to remove unwanted noise is based on the developers training the algorithm to differentiate between desirable and undesirable elements of an audio file. Armed with this knowledge it can break the file down into very small elements and make decisions on what to keep and what to remove.

To some, these kinds of technologies hold a lot of negative connotations. Its easy to write off smart plugins as automated music-making tools ones that take the human skill out of music production. Probably the most controversial is LANDR, the AI-based online mastering service that claims to be able to provide a service traditionally seen as a dark art requiring years of training and a studio full of vintage gear.

At their best, AI-powered plugins tend to support the creative decisions of the music maker, rather than attempt to overrule them. In the case of mixing tools, the tech is best thought of as a modern take on the usual stock presets found in many plugins. As you might turn to a kick insert preset in a compressor plugin as a starting point, a smart plugins AI-powered compressor settings for your kick will likely provide a rough, convenient approximation of whats needed that the user can adjust to taste.

iZotope are relatively old hands when it comes to making use of AI and machine learning. You can find variations on these ideas present in Ozones Mastering Assistant or the smart features of Neoverb. RX is probably the companys most powerful deployment of modern tech, though.

This audio restoration tool uses machine learning to offer smart suggestions on how to clean up and improve audio. It works remarkably well too. Its thanks to this tech that RX keeps getting more and more effective, making it a must for studio, TV and other audio editing applications.

Focusrites recently-launched range of plugins are powered by tech from AI-specialists Sonible, whose Smart series of mixing tools could warrant inclusion in this list too. The reason weve opted for Focusrites take, however, is that these tools are an excellent example of how despite sounding complex intelligent features can actually help to make mixing tools far simpler and more user-friendly.

The four plugins in the range, focusing on EQ, compression, reverb and spectral ducking, each use their AI tools to help apply context-specific presets that can gently steer even total beginners toward the right settings for the job.

With Playbeat, Audiomodern apply an algorithm-driven approach to drum sequencing. On the surface, the plugin functions like a lot of other software drum machines. Users can import samples and sequence them across an eight-track step sequencer. There are parameters for varying pitch, level, flams, pan position, etc.

Where Playbeat is unique, however, is in its algorithms that can be used to randomise or remix a pattern based on current groove. This is where the intelligent element of design lies rather than simply randomise hits and parameters, it makes creative decisions inspired by the existing pattern.

RipX is divided into two versions DeepRemix and DeepAudio. The former of these promises the ability to split a fully mixed and mastered audio file down into individual instrument stems. Does it always work perfectly? No. But its still remarkably impressive, particularly when it comes to working with simple band material (classic rock and pop tracks, for example).

Its functionality relies on machine learning to intelligently identify different elements within an audio file. The pricier DeepRemix does the same, but adds some impressive editing tools too. We particularly like the ability to isolate and edit noise elements.

Atlas uses AI to take the pain out of wading through your unwieldy drum sample library. It works by analysing your sample folders and creating an elegant map coloured nodes that create clusters of samples grouped by sound-type and tone.

Even if you import a disorganised bundle of one-shots, melodic sounds and loops, Atlas will filter the non-percussive sounds to leave neatly-organised maps of beat hits. This functionality is paired with a slick, pad-focused drum machine and step sequencer. Theres a good level of onboard sample editing too, and those smart features make it easy to swap sounds on-the-fly.

TAIP is an interesting marriage between modern tech and vintage effects. The concept itself is nothing new a tape emulation that aims to impart the desirable inconsistencies of analogue tape machines. However, the approach taken is a little different.

According to Baby Audio, rather than use straight DSP, TAIP makes use of AI/neural networks to accurately decipher the sonic qualities that make a tape machine sound and behave in the way it does. This is done by feeding an algorithm with examples of dry and tape-processed audio in order for it to learn the precise differences between the analogue and digital versions of the audio.

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6 AI-powered intelligent plugins that could change the way you make music - MusicRadar

MONTRAL, Jan. 27, 2022 /CNW Telbec/ - TheGlobal Partnership on Artificial Intelligence (GPAI) has announced thatMila researcher Catherine Rgis, full professor at theUniversity of Montral Law Faculty and a Canada Research Chair, is the new co-chair of its working group on responsible AI. Her term will extend until 2024. The GPAI was established in 2020 to support collaboration among experts from 25 countries and promote responsible practices in artificial intelligence.

"We are grateful for this recognition of Qubec expertise in responsible artificial intelligence," says Benjamin Prud'homme, Executive Director, AI for Humanity at Mila. "As a legal scholar with expertise in AI governance and regulation, Catherine Rgis is an outstanding choice for this position."

"The priorities for 2022 will include ensuring that AI development respects human rights and encouraging responsible innovation," explains Catherine Rgis. "We must also work to make sure AI development is equitable and inclusive."

The other co-chair of the working group will be Raja Chatila of France, emeritus professor of robotics, artificial intelligence and ethics at Sorbonne University.

The working group on responsible AI is conducting several projects on timely issues, including:

SOURCE Mila - Quebec AI Institute

For further information: Diep Truong, 514 436-2121, [emailprotected]

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Catherine Rgis to co-chair the Global Partnership on Artificial Intelligence Working Group on Responsible AI - Canada NewsWire

Opinions expressed by Entrepreneur contributors are their own.

A quantum computer is a machine that uses the laws of quantum theory to solve problems made harder by Moore's law (the number of transistors in a dense integrated circuit doubles about every two years). One example is factoring large numbers. Traditional computers are limited to logical circuits with several tens of transistors, while the number of transistors in a quantum processor may be on the order of one to twomillion. Meaning, these computers will have exponential power, solving problems that traditional computation can't even identify or create solutions for.

In the near future, quantum computers will be so advanced that they will have the capability to simulate very complicated systems. This could be used for simulations in physics, aerospace engineering, cybersecurityand much more. However, once this computer is built, it has the potential to unraveldata encryption protocols. It could also potentially compromise air gaps due to its ability to scan vast distances for nearby networked devices or applications that are open. This means that it can become even simpler for external hackers. Theymay already haveaccess to your computer or computer system via other avenues,like vulnerabilities in web browsers. Theycould find it much easier because you're not locking up all the doors.

Quantum computers point to a radically new understanding of computing. An understandingthat could eventually be used to unlock problems now thought completely intractable. For now, the field seems ripe with potential. Scientists working on quantum computing call it one of the most interesting theoretical toolsin artificial intelligence. Think of it as an incredibly powerful calculator programmed with deep domain expertise. Quantum computers promise answers to all sorts of mathematical, scientificand medical questions humans would never have the guts to tackle otherwise. They promise profound breakthroughs in imaging that will rival even experimental intracellular MRI scans; they may help crack wide-ranging databases that are currently unbreakable orthey might pick up scant details like geological signatures warning us about tsunamis long before they happen.

Quantum computers can theoretically be programmed to solve any complex computational problem. But, the act of programming the computer is so expensive and inflexible that someone would need to program it with all possible solutions. Quantum computers threaten everything. The worst part is that security experts can't ever say for sure what you can do to protect against their programming capabilities. They do know, however, that it's possible to reprogram them just as we would with a normal computer. It's just that the task is so complex and difficult that programming would be such a high-level security risk, it might as well never exist.

What does this all mean? It means we need to develop some sort of encryption technology on our smaller devices so not even those who hold all the worlds data can see or access it. Quantum computers work differently than traditional computers. That gives the maker of a quantum computer more control than with a conventional computer. They can do things like reverse time and process large data with greater speed. The manufacturer will program the machine before release, which also comes with certain risks. Ifthey change their mind and reprogramit per client needs, they put themselves at risk for security breaches. The catch is that the cryptography keys are only secure if you keep them secret. The slightest leak say a pinhole camera across the table from something like a quantum computeror a phone call or email intercepted while being decrypted would enable an adversary to not just unscramble your message but steal your keys. The threat made by quantum computing has been speculated since before it was even technologically feasible to build a quantum computer. But now that were nearly there, the situation might be even more direthan you can imagine.

Related:How Will The World Look Like In 2025 And TheFutureOf ...

As quantum computers allow for more efficient algorithms, the dangers of hacking increase. Such security risks have been a top priority at Google. They havehigh expectations for what approach they will take to create their future quantum machine. In the meantime, DARPA (Defense Advanced Research Projects Agency) has set out grand challengesfor computer science with a hefty $2 million prize. DARPA's goal is to keep U.S. cyber strength relevant amid the rapid decline in Moore's Law and potential loss of global technological leadership. If quantum computers proliferate, they will threaten everything not just bank records and medical documents, but everything. They represent a security leak so fundamental that it could be worse than the apocalypse. The quantum computer poses a possible threat to the infrastructure of the United States. Yet the American authorities do not have enough measures in place to stop this type of danger. One way that they can defend themselves is by inventing new safety standards that work with the current technologies.

Whenever quantum computing matures, however, it will present a vigorous challenge. Computer scientists will need to develop the protocols and protections necessary to ensure security for this emerging technology. If these precautions are not taken, quantum computing could lead to disastrous outcomes in cyber security. There needs to be a protocol developed to provide security for quantum computers. Hackers will be able to access and disrupt live systems, which calls for an urgent need of advancements in cyber security. These new systems can't just implement existing protection protocols because they're not fully developed yet. The cost of research and development is high and the profits once the product is finished are relatively low.

Quantum computing is a hot topic at this moment in time that will impact society in a way we can't even predict if we don't acknowledge its significance now. Most computers today work in accordance with digital signals. If someone tries to hack the computer, it will change that digital signal into another form or cancel it out, which can be easily noticed. However, quantum computers use quantum bits forcalculations. Theyare tied together in a way that makes them so sensitive to changes in information that they are exponentially more vulnerable to hacks than digital computers. If someone manages to hack a quantum computer though not yet possible it would have serious implications for maintaining our safety standards.

Related:Thanks to Blockchain, Decentralization -- and Data Security -- Are ...

If the leaked NSA documents are to be believed, then we may be in for a rude awakening when quantum computers become technologically feasible. These machines will be able to perform calculations in far less time than any conventional computerand render our currentencryptions ineffectual. The leaks claim that in 30 years, two medium-sized quantum computers would be able to even break the security of RSA (cryptosystem) which is currently set at 2048 bits.

Any business that relies on modern cryptography is at risk of being hacked in the near future. But what can companies do to protect themselves? As it turns out, there are some pretty straightforward solutions which firms can preserve (or improve) security amid all this hullabaloo with quantum computing. The authors recommend investing in encryption techniques like Bitcoin, the blockchainand the TLS (Transport Layer Security).

In simple terms, quantum computers process information differently from today's digital computers. This is because of their ability to have bits which sit in more than one state simultaneously, meaning they can perform many calculations at a time. In a future dominated by quantum computing, all regular computing will be made virtually obsolete. Hackers will be able to access the deepest secrets of companies without needing a password. To avoid this fate, companies need to embrace encryption techniques that guard against quantum technology, but they cannot afford to stop innovating too drastically.

The looming potential threat of quantum computing should be taken seriously, but this doesn't mean you should panic. The best way to protect yourself is to plan ahead and think about possible solutions. Incorporating elements of quantum cryptography may not always be possible for every client because of the cost. But, it could help secure an important client who cannot risk future interference in their sensitive operations.

Related:How Companies Can Utilize AI andQuantumTechnologies to ...

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Quantum Computing Threatens Everything Could it be Worse Than the Apocalypse? - Entrepreneur

Atom Computing

Atom Computing, a quantum computing company headquartered in Berkeley, California, seems to be on the fast track for funding.

This week Atom announced it had secured$60MSeries B round of financing led by Third Point Ventures. The round also included Prime Movers Lab and insiders Innovation Endeavors, Venrock, and Prelude Ventures.

Atom was founded in 2018 with $5M in seed funds by Benjamin Bloom and Jonathan King. Over two years, the duo used those funds to secretly staff and build a quantum computer with a unique technology. What set Atoms computer apart from other quantum machines was that it was the first quantum computer to use nuclear-spin qubits created from optically-trapped neutral atoms.

First-Generation Quantum Computer, Phoenix

In July 2021, Atom Computingreceived an additional $15M in Series A funding from investorsVenrock, Innovation Endeavors, and Prelude Ventures, plus three grants from the National Science Foundation.

According to a statement on Atom's press release by Rob Hays, Atom Computing's president and CEO, there was no shortage of investment interest. "We've seen a tremendous amount ofinvestor interest in what many are starting to believe is a more promising way to scale quantum computers neutral atoms, he said. Our technology advancements and this investment give us the runway to continue our focus on delivering the most scalable and reliable quantum computers."

Whats different about its technology

Most of todays quantum computers use two types of qubits, either superconducting (IBM & Google) or trapped-ion (Quantinum or IonQ). Amazon doesnt yet have a quantum computer, but it plans to build one using superconducting hardware. In contrast, Psi Quantum and Xanadu use photons of light that act as qubits.

Atom computing chose to use a different technology -nuclear-spin qubits made from neutral atoms.Phoenix, the name of Atoms first-generation, gate-based quantum computer platform, uses 100 optically trapped qubits.

These qubits are created from an isotope of Strontium, a naturally occurring element considered to be a neutral atom. Goingdeeper, neutral atoms have equal numbers of protons and electrons. However, isotopes of Strontium have varying numbers of neutrons. These differences in neutrons produce different energy levels in the atom that allow spin qubits to be created. Atom Computing uses the isotope Strontium-87 and takes advantage of its unique energy levels to create spin qubits.

It is important for qubits to remain in a quantum state long enough to complete running the quantum circuits. The time that a qubit retains its quantum state is called its coherence time. Neutral atom qubits have a longer coherence time than most other qubit technologies.

Lasers instead of wires are used for precision control of the strontium-87 qubits. Lasers eliminates wiring, which can create radiation and noise that negatively affects coherence.

There are many other technical reasons for using neutral atom spin qubits but beyond the scope of this article.

Second generation plans

Artist rendering of Atom Computings second-generation quantum

With its latest $60M Series B funding, Atom Computing plans to build a larger, second-generation neutral-atom quantum computer. Many additional qubits will give the system increased computational ability. Atom Computing is currently likely to have undisclosed customer trials and use cases in progress. However, we expect new and more significant use cases to be publicly announced once the new quantum system is operational.

Patrick Moorhead, president and chief analyst of Moor Insights and Strategy, said, Qubit coherence, fidelity, and scalability are essential factors for achieving quantum advantage. Atom Computing has already demonstrated that Phoenix, its first-generation 100+ nuclear-spin qubit quantum processor, has the potential to check all those boxes. With the additional $60M Series B funding, I believe Atom could build a large qubit, second-generation quantum system that either brings it to the edge of quantum advantage or possibly even achieves it.

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Note: Moor Insights & Strategy writers and editors may have contributed to this article.

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Atom Computing Plans To Build A Bigger And Better High-Tech Quantum Computer With Its Latest $60 Million Series B Funding - Forbes

In the fall of 2019, Google told the world it had reached quantum supremacy.

It was a significant scientific milestone that some compared to the first flight at Kitty Hawk. Harnessing the mysterious powers of quantum mechanics, Google had built a computer that needed only three minutes and 20 seconds to perform a calculation that normal computers couldnt complete in 10,000 years.

But more than two years after Googles announcement, the world is still waiting for a quantum computer that actually does something useful. And it will most likely wait much longer. The world is also waiting for self-driving cars, flying cars, advanced artificial intelligence and brain implants that will let you control your computing devices using nothing but your thoughts.

Silicon Valleys hype machine has long been accused of churning ahead of reality. But in recent years, the tech industrys critics have noticed that its biggest promises the ideas that really could change the world seem further and further on the horizon. The great wealth generated by the industry in recent years has generally been thanks to ideas, like the iPhone and mobile apps, that arrived years ago.

Have the big thinkers of tech lost their mojo?

The answer, those big thinkers are quick to respond, is absolutely not. But the projects they are tackling are far more difficult than building a new app or disrupting another aging industry. And if you look around, the tools that have helped you cope with almost two years of a pandemic the home computers, the videoconferencing services and Wi-Fi, even the technology that aided researchers in the development of vaccines have shown the industry hasnt exactly lost a step.

Imagine the economic impact of the pandemic had there not been the infrastructure the hardware and the software that allowed so many white-collar workers to work from home and so many other parts of the economy to be conducted in a digitally mediated way, said Margaret OMara, a professor at the University of Washington who specializes in the history of Silicon Valley.

As for the next big thing, the big thinkers say, give it time. Take quantum computing. Jake Taylor, who oversaw quantum computing efforts for the White House and is now chief science officer at the quantum start-up Riverlane, said building a quantum computer might be the most difficult task ever undertaken. This is a machine that defies the physics of everyday life.

A quantum computer relies on the strange ways that some objects behave at the subatomic level or when exposed to extreme cold, like metal chilled to nearly 460 degrees below zero. If scientists merely try to read information from these quantum systems, they tend to break.

While building a quantum computer, Dr. Taylor said, you are constantly working against the fundamental tendency of nature.

The most important tech advances of the past few decades the microchip, the internet, the mouse-driven computer, the smartphone were not defying physics. And they were allowed to gestate for years, even decades, inside government agencies and corporate research labs before ultimately reaching mass adoption.

The age of mobile and cloud computing has created so many new business opportunities, Dr. OMara said. But now there are trickier problems.

Still, the loudest voices in Silicon Valley often discuss those trickier problems as if they were just another smartphone app. That can inflate expectations.

People who arent experts who understand the challenges may have been misled by the hype, said Raquel Urtasun, a University of Toronto professor who helped oversee the development of self-driving cars at Uber and is now chief executive of the self-driving start-up Waabi.

Technologies like self-driving cars and artificial intelligence do not face the same physical obstacles as quantum computing. But just as researchers do not yet know how to build a viable quantum computer, they do not yet know how to design a car that can safely drive itself in any situation or a machine that can do anything the human brain can do.

Even a technology like augmented reality eyeglasses that can layer digital images onto what you see in the real world will require years of additional research and engineering before it is perfected.

Andrew Bosworth, vice president at Meta, formerly Facebook, said that building these lightweight eyeglasses was akin to creating the first mouse-driven personal computers in the 1970s (the mouse itself was invented in 1964). Companies like Meta must design an entirely new way of using computers, before stuffing all its pieces into a tiny package.

Over the past two decades, companies like Facebook have built and deployed new technologies at a speed that never seemed possible before. But as Mr. Bosworth said, these were predominantly software technologies built solely with bits pieces of digital information.

Building new kinds of hardware working with physical atoms is a far more difficult task. As an industry, we have almost forgotten what this is like, Mr. Bosworth said, calling the creation of augmented reality glasses a once-in-a-lifetime project.

Technologists like Mr. Bosworth believe they will eventually overcome those obstacles and they are more open about how difficult it will be. But thats not always the case. And when an industry has seeped into every part of daily life, it can be hard to separate hand-waving from realism especially when it is huge companies like Google and well-known personalities like Elon Musk drawing that attention.

Many in Silicon Valley believe that hand-waving is an important part of pushing technologies into the mainstream. The hype helps attract the money and the talent and the belief needed to build the technology.

If the outcome is desirable and it is technically possible then its OK if were off by three years or five years or whatever, said Aaron Levie, chief executive of the Silicon Valley company Box. You want entrepreneurs to be optimistic to have a little bit of that Steve Jobs reality-distortion field, which helped to persuade people to buy into his big ideas.

The hype is also a way for entrepreneurs to generate interest among the public. Even if new technologies can be built, there is no guarantee that people and businesses will want them and adopt them and pay for them. They need coaxing. And maybe more patience than most people inside and outside the tech industry will admit.

When we hear about a new technology, it takes less than 10 minutes for our brains to imagine what it can do. We instantly compress all of the compounding infrastructure and innovation needed to get to that point, Mr. Levie said. That is the cognitive dissonance we are dealing with.

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Why Is Silicon Valley Still Waiting for the Next Big Thing? - The New York Times

Cambridge-based quantum engineering company Riverlane is at the heart of two related initiatives to troubleshoot problems and advance risk-free adoption worldwide.

It has head-hunted leading scientist Dr Earl Campbell to accelerate efforts to solve quantum error correction and only last month joined an influential consortium to build error corrected quantum processor.

As head of architecture, Dr Campbell will lead technical development to support the operating system for fault-tolerant quantum computers.

He joins Riverlane from Amazon Web Services Quantum Computing group, and has held a number of academic positions over the past 16 years. His game-changing efforts include leading contributions to quantum error correction, fault-tolerant quantum logic and compilation and quantum algorithms.

He has also made pioneering contributions to random compilers, including the qDRIFT algorithm, which is the only known efficient method for simulating systems with highly complex interactions.

Additionally, while working with IBM and University College London, Earl contributed to the development of near-Clifford emulators that were integrated into Qiskit IBMs open-source software development kit for quantum computers.

At Amazon Web Services he was a leading contributor to its paper proposing a novel quantum computing architecture and established a team working on quantum algorithms.

At Riverlane he will be working alongside leaders who have joined from Microsoft, ARM, Samsung, Intel and the White House! Backed by some of Europes leading venture-capital funds and the University of Cambridge, Riverlane is bringing together leading talent from the worlds of business, academia, and industry to design its modular operating system to work with all hardware providers, whatever the type of qubit.

Riverlane has already partnered with a third of the worlds quantum computing hardware companies, and has successfully tested Deltaflow.OS with multiple hardware approaches, including trapped ions and superconducting circuits.

Dr Campbell said: Error correction is the next defining challenge in quantum computing and we will need to deliver fast, effective software to solve it. Over the past 16 years, I have been tackling questions like this as an academic and Im looking forward to putting theory into practice.

Ive followed Riverlane since its early days and Ive always been drawn to challenging work with the promise of delivering widespread social and commercial impact. Im excited to join a diverse team with a proven track record in developing software used by hardware companies around the world.

Steve Brierley, CEO and founder of Riverlane added: Solving error correction will be key to unlocking quantum usefulness across a range of foundational challenges, including clean energy, drug discovery, material science, and advanced chemistry.

Were delighted that Earl is bringing his world-class expertise in this challenge to the Riverlane team to accelerate our efforts and unlock the potential of this technology.

Just before Christmas, Riverlane joined a 7.5 million consortium to build an error corrected quantum processor working with a range of UK partners, including Rolls-Royce to apply this toward new applications in the aerospace industry. The funding comes via the UK governments National Quantum Technologies Programme.

The project, led by quantum computer manufacturer Universal Quantum, calls on Riverlanes software and expertise to tackle quantum error correction on a trapped-ion quantum computer.

Error correction is a crucial step in unlocking the promise of fault tolerant quantum computers capable of a range of transformative applications, and is at the core of everything Riverlane does.

The work with Rolls-Royce will explore how quantum computers can develop practical applications toward the development of more sustainable and efficient jet engines.

This starts by applying quantum algorithms to take steps to toward a greater understanding of how liquids and gases flow, a field known as fluid dynamics. Simulating such flows accurately is beyond the computational capacity of even the most powerful classical computers today.

The consortium also includes: academic researchers from Imperial College London and the University of Sussex; the Science and Technology Facilities Council (STFC) Hartree Centre; supply chain partners Edwards, TMD Technologies and Diamond Microwave; and commercialisation and dissemination experts Sia Partners and Qureca.Fluids behave according to a famous set of partial differential equations called the Navier-Stokes equations, the solutions to which are important for aircraft and engine design, as well as understanding ocean currents and predicting the weather.

Classical computers can take months or even years to solve some types of these equations but recent research has shown that quantum computers could find the solutions much more quickly.

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Riverlane taking quantum computing to fresh frontiers | Business Weekly - Business Weekly