Monthly Archives: September 2021

You may well have seen sci-fi movies or television shows where the protagonist asks to zoom in on an image and enhance the results revealing a face, or a number plate, or any other key detail and Google's newest artificial intelligence engines, based on what's known as diffusion models, are able to pull off this very trick.

It's a difficult process to master, because essentially what's happening is that picture details are being added that the camera didn't originally capture, using some super-smart guesswork based on other, similar-looking images.

The technique is called natural image synthesis by Google, and in this particular scenario, image super-resolution. You start off with a small, blocky, pixelated photo, and you end up with something sharp, clear, and natural-looking. It may not match the original exactly, but it's close enough to look real to a pair of human eyes.

(Google Research)

Google has actually unveiled two new AI tools for the job. The first is called SR3, or Super-Resolution via Repeated Refinement, and it works by adding noise or unpredictability to an image and then reversing the process and taking it away much as an image editor might try to sharpen up your vacation snaps.

"Diffusion models work by corrupting the training data by progressively adding Gaussian noise, slowly wiping out details in the data until it becomes pure noise, and then training a neural network to reverse this corruption process," explain research scientist Jonathan Ho and software engineer Chitwan Saharia from Google Research.

Through a series of probability calculations based on a vast database of images and some machine learning magic, SR3 is able to envisage what a full-resolution version of a blocky low-resolution image looks like. You can read more about it in the paper Google has posted on arXiv.

The second tool is CDM, or Cascaded Diffusion Models. Google describes these as "pipelines" through which diffusion models including SR3 can be directed for high-quality image resolution upgrades. It takes the enhancement models and makes larger images out of it, and Google has published a paper on this too.

CDM in action. (Google Research)

By using different enhancement models at different resolutions, the CDM approach is able to beat alternative methods for upsizing images, Google says. The new AI engine was tested on ImageNet, a gigantic database of training images commonly used for visual object recognition research.

The end results of SR3 and CDM are impressive. In a standard test with 50 human volunteers, SR3-generated images of human faces were mistaken for real photos around 50 percent of the time and considering a perfect algorithm would be expected to hit a 50 percent score, that's impressive.

It's worth reiterating that these enhanced images aren't exact matches for the originals, but they're carefully calculated simulations based on some advanced probability maths.

Google says the diffusion approach produces better results than alternative options, including generative adversarial networks (GANs) that pit two neural networks against each other to refine results.

(Google Research)

Google is promising much more from its new AI engines and associated technologies not just in terms of upscaling images of faces and other natural objects, but in other areas of probability modeling as well.

"We are excited to further test the limits of diffusion models for a wide variety of generative modeling problems," the team explains.

See the rest here:

Google's Incredible New Photo AI Makes 'Zoom And Enhance' a Real Thing - ScienceAlert

Hong Kongs long awaited M+ Museum has announced an opening date. When the institution dedicated to modern and contemporary visual culture finally opens its doors on November 12, it will be against a very different political backdrop than its leaders anticipated when M+ was first conceived more than a decade ago.

Evidence of this shift is already evident on the museums newly launched website, where an image of Ai Weiweis photograph of Tiananmen Square has been removed while it awaits review by the authorities,Artnet News has learned.

Earlier this spring, pro-Beijing politicians had accused Ais Study of Perspective: Tiananmen (1997)which depicts the Chinese dissident artist raising a middle finger at Beijings Tiananmen Squareof spreading hatred against China under the countrys national security law, which went into effect in Hong Kong last June.

Another work by Ai, Map of China (2003), has also been censored online. That sculpture, a 3D map of the country made of wood salvaged from demolished Qing Dynasty temples, aims to celebrate Chinas cultural and ethnic diversity. The sculpture and photograph are part of the M+ Sigg Collection, a major Chinese art trove donated to the museum by Swiss entrepreneur Uli Sigg.

Both images could be seen on the beta version of the M+ collection website, but were no longer available when the final site went live on August 10.

M+ is reviewing the treatment of certain images of works having regard to the advice obtained from relevant authorities including the Office for Film, Newspaper and Article Administration, a spokesperson for the museum told Artnet News. The images concerned are not uploaded pending completion of the review.

A screenshot of M+s website, with images of some Ai Weiwei works missing.

Many images of works by Ai are accessible on the website, including Still Life, an installation comprising thousands of axes from the Stone Age that was exhibited when the M+ Sigg Collection was first unveiled in Hong Kong in 2016, as well as other pieces from the Study of Perspective series, including Bundeshaus Bern (1999) and White House (1995).

Ai questioned the inconsistent treatment of the series. Why is M+ not showing Tiananmen but keeping White House? the artisttold Artnet News. (Ai recently wrote an op ed for Artnet News about M+s decision not to show the work in its opening show.)

Hong Kongs Office for Film, Newspaper and Article Administration is responsible for enforcing the film classification system under the Film Censorship Ordinance, controlling the publication of obscene and indecent articles, and the registration of local newspapers. The government proposed in August to amend the Film Censorship Ordinance, giving the chief secretary, the citys number two executive, power to revoke any approval given to a film should its exhibition be contrary to the interests of national security.

Ai Weiwei, Study of Perspective: Tiananmen (1997). M+ Sigg Collection, Hong Kong. By donation, Ai Weiwei.

In addition to the two works by Ai, a number of other objects in the M+ collection are not shown on the website, including some of those by Kacey Wong, who is known for his political art and recently left Hong Kong for Taiwan in self-imposed exile. However, some works that might be considered politically sensitive, such as Liu Heung-Shings photographic series China After Mao and images depicting the summer of 1989 in Beijing following the Tiananmen crackdown, are accessible.

The soon-to-open museum stated that digitization of its 8,000-object-strong collection is an ongoing effort and that the collection will be updated periodically as new works, information and intellectual property rights become available.

The museums inaugural exhibitions will likely be closely watched by Chinese authorities for evidence of its compliance with the rulesand by the international art community to gauge its willingness to confront sensitive subjects. The museum announced on Wednesday that its debut presentations willfeature around 1,500 works spanning fine art, film, design, architecture, and archival items.

The six thematic exhibitions will includea section dedicated to the evolution of Hong Kongs visual culture from the 1960s to the present; a special presentation of the M+ Sigg Collection titled From Revolution to Globalization; and a chronological survey of Chinese art from the 1970s to the 2000s.

M+ will also presentAsian Fields, a monumental installation that comprises tens of thousands of clay figurines by the British artist Antony Gormley, who created the work with more than 300 villagers from Guangdong in the span of five days in 2003.

Compared to leading modern art museums in the West, M+ will look very different, because our vantage point on this side of the world is distinct,Doryun Chong, deputy director of the museum, said in a statement announcing the inaugural program. This is a multidisciplinary contemporary collection, grounded in Asia and like no other in the world.

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Hong Kongs M+ Museum Has Removed Ai Weiweis Famous Tiananmen Square Photo From Its Website While It Awaits Government Review - artnet News

CalypsoAI and ECS announced a partnership to support the advancement of safe and secure artificial intelligence (AI) infrastructure across the U.S. federal government.

The partnership will see CalypsoAI leverage its AI safety and security software to expand ECS testing capabilities for government customers. CalypsoAI is providing ECS with proprietary capabilities for trustworthy model development, and novel testing and evaluation (T&E). This collaboration will accelerate the deployment of trusted and responsible AI across federal agencies, such as the U.S. Department of Defense, the U.S. Department of Homeland Security, the U.S. Department of Health and Human Services.

As demand for AI-enabled capabilities increases across the federal government, ensuring trust and transparency of these systems will be essential to ensuring the widespread adoption of game-changing AI technology by civil servants, intelligence professionals, and warfighters, said Neil Serebryany, CEO and Founder of CalypsoAI. We look forward to deploying our industry-leading AI security technology across ECS AI platforms to ensure federal agency missions are supported responsibly, from technology development through deployment.

AI safety and security is a priority issue for senior government leaders, such as Deputy Secretary of Defense, Dr. Kathleen Hicks. In May, she released a memo articulating the imperative for the U.S. Department of Defense to create a responsible AI framework to support safe and secure AI development and deployment. CalypsoAIs partnership with ECS supports this framework by further expanding access to AI T&E capabilities to federal customers, which will give them the tools they need to develop and field safe AI capabilities.

We have built the critical open ecosystem for assured AI for the speed, security, and scale of government needs, said Aaron Burciaga, vice president of data & artificial intelligence at ECS. From real-time edge analytics for the warfighter to massive data operations for commerce, we have engineered the future with CalypsoAI. Together we ensure adaptive solutions, responsible data operations, explainable algorithms, and secure environments for the ongoing digital revolution centered on information technology and intelligence technology.

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CalypsoAI and ECS support the advancement of secure AI infrastructure for government customers - Help Net Security

Photo: Martin Meissner (AP)

Dont worry, humansartificial intelligence systems arent taking over the world yet. They cant even appear as inventors on U.S. patents.

U.S. federal judge Leonie Brikema ruled this week that an AI cant be listed as an inventor on a U.S. patent under current law. The case was brought forward by Stephen Thaler, who is part of the Artificial Inventor Project, an international initiative that argues that an AI should be allowed to be listed as an inventor in a patent (the owner of the AI would legally own the patent).

Thaler sued the U.S. Patent and Trademark Office after it denied his patent applications because he had listed the AI named DABUS as the inventor of a new type of flashing light and a beverage container. In various responses spanning several months, the Patent Office explained to Thaler that a machine does not qualify as an inventor because it is not a person. In fact, the machine is a tool used by people to create inventions, the agency maintained.

Brikema determined that the Patent Office correctly enforced the nations patent laws and pointed out that it basically all boils down to the everyday use of language. In the latest revision of the nations patent law in 2011, Congress explicitly defined an inventor as an individual. The Patent Act also references an inventor using words such as himself and herself.

By using personal pronouns such as himself or herself and the verb believes in adjacent terms modifying individual, Congress was clearly referencing a natural person, Brikema said in her ruling, which you can read in full at the Verge. Because there is a presumption that a given term is used to mean the same thing throughout a statute, the term individual is presumed to have a persistent meaning throughout the Patent Act.

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The judge also rejected Thalers claim that the Patent Office had to provide evidence that Congress did not want to exclude AI systems from being inventors.

Furthermore, Brikema stated that the nature of an inventor has already been examined in federal courts, which have ruled that neither companies nor states can claim to be inventors on a patent.

For his part, Thaler also tried to argue that the court should respect Congress intent to create a system that would encourage innovation.

Allowing patents for AI-Generated Inventions will result in more innovation. It will incentivize the development of AI capable of producing patentable output by making that output more valuable Thaler said. By contrast, denying patent protection for AI-Generated Inventions threatens to undermine the patent system by failing to encourage the production of socially valuable inventions.

Nonetheless, Thaler didnt have luck with that argument, either. Brikema said that these were policy considerations and thus must be dealt with by Congress, not the courts.

And its not like the Patent Office is refusing to consider what role, if any, AI should have in patents. It has requested comments artificial intelligence in patent policy and reported that the majority of responses reflected the belief that current AI could neither invent nor author without human intervention.

Ryan Abbott, a law professor who oversees the Artificial Inventor Project, told Bloomberg the group would appeal. Although Brikema squashed all of the projects arguments, she didnt say an AI could never be listed as an inventor.

As technology evolves, there may come a time when artificial intelligence reaches a level of sophistication such that might satisfy accepted meanings of inventorship. But that time has not yet arrived, and, if it does, it will be up to Congress to decide how, if it at all, it wants to expand the scope of patent law, Brikema said.

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Judge Says an AI Cant Be an Inventor on a Patent Because Its Not a Person - Gizmodo

DUBLIN--(BUSINESS WIRE)--The "Asset Tracking and AI in Supply Chain Management Market 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This research evaluates asset tracking technologies, solutions, and the overall asset management and logistics ecosystem including major players, strategies and market positioning. The research evaluates the impacts of use case-specific considerations in terms of asset tracking technology and solution selection.

This research also provides an analysis of both fleet-related asset tracking and non-fleet asset tracking markets. Fleet tracking market analysis includes segmentation by IoT-enabled fleet tracking. In terms of non-fleet asset tracking, the research evaluates the market for both living and nonliving things, which have completely different characteristics.

This research also provides detailed analysis and forecasts for AI in SCM by solution (Platforms, Software, and AI as a Service), solution components (Hardware, Software, Services), management function (Automation, Planning and Logistics, Inventory Management, Fleet Management, Freight Brokerage, Risk Management, and Dispute Resolution), AI technologies (Cognitive Computing, Computer Vision, Context-aware Computing, Natural Language Processing, and Machine Learning), and industry verticals (Aerospace, Automotive, Consumer Goods, Healthcare, Manufacturing, and others).

This is the broadest and detailed research of its type, providing analysis across a wide range of go-to-operational process considerations, such as the need for identity management and real-time location tracking, and market deployment considerations, such as AI type, technologies, platforms, connectivity, IoT integration, and deployment model including AI-as-a-Service (AIaaS). Each aspect evaluated includes forecasts from 2021 to 2026 such as AIaaS by revenue in China. It provides an analysis of AI in SCM globally, regionally, and by country including the top ten countries per region by market share.

The research also provides an analysis of leading companies and solutions that are leveraging AI in their supply chains and those they manage on behalf of others, with an evaluation of key strengths and weaknesses of these solutions. It assesses AI in SCM by industry vertical and application such as material movement tracking and drug supply management in manufacturing and healthcare respectively. The research also provides a view into the future of AI in SCM including analysis of performance improvements such as optimization of revenues, supply chain satisfaction, and cost reduction.

Companies Mentioned

Select Research Findings:

Key Topics Covered:

Asset Tracking Market by Infrastructure, Connection Type, Mobility, Location Method, Solution Type, Supporting Tech and Industry Verticals

1. Executive Summary

2. Asset Tracking Market Segmentation

3. Introduction

4. Asset Tracking Solutions

5. Asset Tracking in Industry Verticals

6. Company Analysis

7. Overall Asset Tracking Market Analysis and Forecasts 2021 - 2026

8. Fleet Tracking Market Analysis and Forecasts 2021 - 2026

9. Non-Fleet Asset Tracking Market Analysis and Forecasts 2021 - 2026

10. IoT enabled Fleet Tracking Market Segment 2021 - 2026

11. IoT Enabled Non-Fleet Asset Tracking 2021 - 2026

12. Video Safety in Fleet Tracking Market 2021 - 2026

13. Emerging Technologies in Fleet Tracking Market 2021 - 2026

14. Slap-and-Track Asset Tracking Solutions Market 2021 - 2026

15. Living Creature Tracking Market 2021 - 2026

16. Conclusions and Recommendations

AI in Supply Chain Management Market by Technology, Processes, Solutions, Management Function, Deployment Model, Business Type and Industry Verticals

1.0 Executive Summary

2.0 Introduction

3.0 AI in SCM Challenges and Opportunities

4.0 Supply Chain Ecosystem Company Analysis

5.0 AI in SCM Market Case Studies

6.0 AI in SCM Market Analysis and Forecasts 2021 - 2026

7.0 Summary and Recommendations

For more information about this report visit https://www.researchandmarkets.com/r/z5g9uh

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Global Asset Tracking and AI in Supply Chain Management Market (2021 - 2026) - Featuring 3M, Adidas and ARI Fleet Among Others -...

AI holds great promise to increase the quality and reduce the cost of health care in developed and developing countries. But one obstacle to using it is patients dont trust it. One key reason is they perceive medical AI to be a black box and they think they know more about physicians decision-making process than they actually do, the authors research found. A remedy: Provide patients with an explanation of how both types of care providers make decisions.

Artificial intelligence-enabled health applications for diagnostic care are becoming widely available to consumers; some can even be accessed via smartphones. Google, for instance, recently announced its entry into this market with an AI-based tool that helps people identify skin, hair, and nail conditions.A major barrier to the adoption of these technologies, however, is that consumers tend to trust medical AI less than human health care providers. They believe that medical AI fails to cater to their unique needs and performs worse than comparable human providers, and they feel that they cannot hold AI accountable for mistakes in the same way they could a human.

This resistance to AI in the medical domain poses a challenge to policymakers who wish to improve health care and to companies selling innovative health services. Our research provides insights that could be used to overcome this resistance.

In a paper recently published in Nature Human Behaviour, we show that consumer adoption of medical AI has as much to do with their negative perceptions of AI care providers as with their unrealistically positive views of human care providers. Consumers are reluctant to rely on AI care providers because they do not believe they understand or objectively understand how AI makes medical decisions; they view its decision-making as a black box. Consumers are also reluctant to utilize medical AI because they erroneously believe they better understand how humans make medical decisions.

Our research consisting of five online experiments with nationally representative and convenience samples of 2,699 people and an online field study on Google Ads shows how little consumers understand about how medical AI arrives at its conclusions. For instance, we tested how much nationally representative samples of Americans knew about how AI care providers make medical decisions such as whether a skin mole is malignant or benign. Participants performed no better than they would have if they had guessed; they would have done just as well if they picked answers at random. But participants recognized their ignorance: They rated their understanding of how AI care providers make medical decisions as low.

By contrast, participants overestimated how well they understood how human doctors make medical decisions. Even though participants in our experiments possessed similarly little factual understanding of decisions made by AI and human care providers, they claimed to better understand how human decision-making worked.

In one experiment, we asked a nationally representative online sample of 297 U.S. residents to report how much they understood about how a doctor or an algorithm would examine images of their skin to identify cancerous skin lesions. Then we asked them to explain the human or the algorithmic providers decision-making processes. (This type of intervention that has been used before to shatter illusory beliefs about how well one understands causal processes. Most people, for instance, believe they understand how a helicopter works. Only when you ask them to explain how it works, do they realize they have no idea.)

After participants tried to provide an explanation, they rated their understanding of the human or algorithmic medical decision-making process again. We found that forcing people to explain the human or algorithmic providers decision-making processes reduced the extent to which participants felt that they understood decisions made by human providers but not decisions made by algorithmic providers. Thats becausetheir subjective understanding of how doctors made decisions had been inflated and their subjective understanding of how AI providers made decisions was unaffected by having to provide an explanation possibly because the had already felt the latter was a black box.

In another experiment, with a nationally representative sample of 803 Americans, we measured both how well people subjectively felt that they understood human or algorithmic decision-making processes for diagnosing skin cancerand then tested them to see how well they actually did understand them. To do this, we created a quiz with the aid of medical experts: a team of dermatologists at a medical school in the Netherlands and a team of developers of a popular skin-cancer-detection application in Europe. We found that although participants reported a poorer subjective understanding of medical decisions made by algorithms than decisions made by human providers, they possessed a similarly limited real understanding of decisions made by human and algorithmic providers.

What can policymakers and firms do to encourage consumer uptake of medical AI?

We found two successful, slightly different interventions that involved explaining how providers both algorithmic and human make medical decisions. In one experiment, we explained how both types of providers use the ABCD framework (asymmetry, border, color, and diameter) to examine features of a mole to make a malignancy-risk assessment. In another experiment, we explained how both types of providers examine the visual similarity between a target mole and other moles known to be malignant.

These interventions successfully reduced the difference in perceived understanding of algorithmic and human decision-making by increasing the perceived understanding of the former. In turn, the interventions increased participants intentions to utilize algorithmic care providers without reducing their intentions to utilize human providers.

The efficacy of these interventions is not confined to the laboratory. In a field study on Google Ads, we had users see one of two different ads for a skin-cancer-screening application in their search results. One ad offered no explanation and the other briefly explained how the algorithm works. After a five-day campaign, the ad explaining how the algorithm works produced more clicks and a higher click-through rate.

AI-based health care services are instrumental to the mission of providing high-quality and affordable services to consumers in developed and developing nations. Our findings show how greater transparency opening the AI black box can help achieve this critical mission.

Continued here:

For Patients to Trust Medical AI, They Need to Understand It - Harvard Business Review

The detectors have already made an appearance at Lower.com Field.

COLUMBUS, Ohio Several Ohio stadiums are implementing new security systems designed to detect weapons while simultaneously easing the burden on sports fans.

Evolv makes touchless screening systems for weapons detection. The company uses a combination of advanced sensors and artificial intelligence to specifically detect weapons and not just any metal item going through a detector.

What weve done is weve rethought the entire approach, said Anil Chitkara, co-founder and head of corporate development for Evolv.

The detectors have already made an appearance at Lower.com Field. Josh Glessing, vice president of strategy for Haslam Sports, says the addition was a win-win for everyone, especially the fans who no longer have to slow down or stop unless an alert is set off.

One, we alleviate the stress points of people bunching together and moving slowly through, and two, its a frictionless experience, Glessing said. A lot of people dont realize theyre going through security.

10TV spoke with several fans at a recent Columbus Crew game to gauge their thoughts on the new equipment.

It doesnt bother me because it keeps us all safe and together, Cindy Nauer said. All we can do is try and stay one step ahead.

In regard to walking through metal detectors, Terrell Brett said, Its annoying, but at the same time, Id rather have it depending on if something crazy, with everything going on.

Like its name specifies, Chitkara said the Evolv system will evolve with the changing technology of how guns are made; particularly 3D printed firearms.

As the material and makeup of those weapons change, we bring them into our lab, we test them and we run them through our system and then we improve the algorithm to detect them, said Chitkara. Theres a wide range of weapons that it will detect.

Other central Ohio venues are also implementing new metal detectors at the gates. Fans walking through the gates at Ohio Stadium will see a similar metal detector system when the Buckeyes open their season home opener this coming Saturday.

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New security system using AI to find weapons at several Ohio stadiums - 10TV

New Capabilities Automate User Access and Makes Achieving Zero Trust Easier for the Enterprise

SAN FRANCISCO, September 08, 2021--(BUSINESS WIRE)--ForgeRock, a global digital identity leader, today announced the availability of its latest version of ForgeRock Autonomous Identity designed to help enterprises reduce risk and more efficiently manage workforce access. The companys AI-driven approach to identity governance and administration (IGA) offers new capabilities to help teams heighten security by avoiding excessive access permissions and eliminating orphaned user accounts -- both prime targets for external attackers and insider threats.

Enterprises have long tried to use role-based access control (RBAC) to simplify the process of managing workforce access permissions. However the effectiveness of this approach erodes over time because traditional IGA and RBAC processes lead to over-provisioning of access permissions -- giving access to people who dont need it -- resulting in an increased attack surface. Organizations have traditionally managed access using manual, labor-intensive processes that can no longer scale to meet todays dynamic security requirements.

The AI-Driven Approach to Zero Trust and Role-based Access Control

According to Gartner Inc. research, titled "Modern Approaches to Identity Governance and Administration Role Modeling*," the firm advises that "the process of updating IGA policies and roles should be automated using machine learning (ML) and advanced analytics, so that it leverages additional inputs, such as actual usage, to mitigate over-entitlement and role proliferation."

ForgeRock is doing exactly that with its latest release of Autonomous Identity. The modern IGA solution now leverages artificial intelligence (AI) and machine learning to reduce enterprise risk by discovering role-based access patterns across the entire organization and recommending optimized role structures. These specific role recommendations help ensure that users have the level of access they need while increasing the organizations security posture. This enables organizations to customize their own risk criteria without the need for frequent and laborious data analysis.

Story continues

"ForgeRock Autonomous Identity has always been about helping IT and security teams work smarter," said Peter Barker, Chief Product Officer, ForgeRock. "With this new release of Autonomous Identity, were introducing new role management capabilities that tackle tedious, manual access and governance processes using AI and ML to more quickly identify and eliminate risky access across the entire enterprise. These new features provide an even more powerful way to give companies control of their data and also organize that data with optimized roles to more efficiently manage and govern access."

"Accenture is a strategic ForgeRock partner as well as a customer, so we know firsthand how essential IGA is to keeping enterprises safe from cyber threats," said Rex Thexton, Managing Director, Global Applied Cybersecurity Services Lead, Accenture. "ForgeRock Autonomous Identitys AI-driven analytics allow us to quickly and accurately prevent over-provisioning account access to our more than half a million employees with a much higher degree of confidence. These new features provide a better way to manage user privileges and help organizations have more visibility across their networks so they can proactively identify risks."

The new Forgerock Autonomous Identity capabilities are available now. For more information please visit http://www.forgerock.com.

About ForgeRock

ForgeRock, a global leader in digital identity, delivers modern and comprehensive identity and access management solutions for consumers, employees and things to simply and safely access the connected world. Using ForgeRock, more than a thousand global customer organizations orchestrate, manage, and secure the complete lifecycle of identities from dynamic access controls, governance, APIs, and storing authoritative data consumable in any cloud or hybrid environment. The company is privately held, and headquartered in San Francisco, California, with offices around the world. For more information and free downloads, visit http://www.forgerock.com or follow ForgeRock on social media: Facebook ForgeRock |Twitter @ForgeRock | LinkedIn ForgeRock.

* - Gartner, Modern Approaches to Identity Governance and Administration Role Modeling, by Nat Krishnan, August 12, 2021. ID G00750252

View source version on businesswire.com: https://www.businesswire.com/news/home/20210908005637/en/

Contacts

Stacey HurwitzForgeRockStacey.Hurwitz@forgerock.com

OR

Edelman on behalf of ForgeRockDillon TownselDillon.Townsel@edelman.com

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ForgeRock Autonomous Identity Ushers in a New Era of AI-Driven Identity Governance and Administration - Yahoo Finance

It's something we've always wished we had, and now it's almost here.

Google has revealed their work on a new piece of artificial intelligence (AI) tech that will allow users to zoom in on photos or images without them getting blurry. Instead of getting pixelated the photos will continue to look clean and sharp, kind of like the tech used in crime TV series like Crime Scene Investigations.

Something like this, but not quite:

The new AI engines work based on what's known as diffusion models, and involves a technique known as natural image synthesis.

In this technique, details are added to an image that weren't originally captured by the camera or inserted by whatever software was used to make it. The additional details are added using a mix of clever guesswork and deriving info from other similar-looking images.

Of course, this means that the enhanced photo won't turn out exactly like the original, but you can still expect pixelated or blurry images to be transformed into pictures that you can enjoy and use without worrying how others see them.

With regards to the tools used to make this magic happen, Google has said that they currently employ two techniques.

The first is a diffusion model technique called Super-Resolution via Repeated Refinement (or SR3), and basically works by adding extra noise or unpredictable elements to an image, then reversing the process and fixing the image, just like how a photo editor works to improve any image taken from a camera.

Then by using probability math and looking through a huge library of pre-existing images, SR3 can then better predict what a full, clear image should look like despite how blurry or pixelated the original is.

"Diffusion models work by corrupting the training data by progressively adding Gaussian noise, slowly wiping out details in the data until it becomes pure noise, and then training a neural network to reverse this corruption process," explained members of the Google Research team.

The other tool is known as Cascaded Diffusion Models (or CDM), that works by acting as "pipelines" through which diffusion models like SR3 can be directed for the purpose of upgrading images into high-resolution.

While these all sound extremely technical, Google's progress with these techniques have so far been impressive.

In a test conducted on the gigantic image database ImageNet, Google's new AI engine manage to convince 50 volunteer testers that images of human faces generated by SR3 and CDM were real 50 percent of the time pretty amazing for a bunch of images created by performing complex mathematics.

Currently, it's still not known how or when Google plans to introduce their new engine to the mainstream, although the team have confirmed that they're still working on other exciting technologies related to AI and diffusion models.

"With SR3 and CDM, we have pushed the performance of diffusion models to state-of-the-art on super-resolution and class-conditional ImageNet generation benchmarks," the team said. "We are excited to further test the limits of diffusion models for a wide variety of generative modeling problems."

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Cover image sourced from Kishor on Unsplash. For illustration purposes only.

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Google's new AI will let you zoom into photos without blurring everything - Mashable SE Asia

Related: UAE enjoys tech jobs boom as pandemic recovery gathers pace

Female tech pioneers from the UAE have described their desire to get more girls to learn about artificial intelligence and coding.

They spoke in an online meeting of thought leaders, organised by the British Embassy UAE on Tuesday.

Gamification and using the power of social media were two suggestions on how to encourage more young people to consider a career in tech.

A lot of people think that working in technology is not for them, because it's too hard, or because there are stereotypes that only white men work in the sector

Joysy John, 01Founders

Emirati student, Fatima Ali Aldhuhoori, who was part of her school's prize-winning robotics team and Radhika Iyer, who studied in the UAE before moving to the UK and winning the Amazon Longitude Explorer Prize for tech design, discussed how much they enjoyed using computer science to solve problems.

Globally, these two women are outliers for their generation. Only 18 per cent of girls in tertiary education are pursuing science, technology, engineering, and mathematics studies, compared to 35 per cent of boys, according to the UN children's fund.

Joysy John, the CEO of 01Founders, a free coding school in the UK, told the online meeting about the dire shortage of software engineers and the need for more young people to learn how to work in the digital space.

"A lot of people think that working in technology is not for them, because it's too hard or because there are stereotypes that only white men work in the sector," said Ms John.

"By changing this stereotype and by having more role models, we can actually change the world in terms of who gets to build the algorithms that are used by everyone."

There is a shortage of women working in tech, although this could soon change, as 56 per cent of the UAE's graduates in STEM courses at government universities are women. Pawan Singh / The National

The UK has placed girls education at the heart of its current presidency of the G7.

In July, the country hosted the Global Education Summit in London and raised $4 billion for global education.

The UAE was the biggest donor from the region at that event, and will host the RewirEd education conference at Expo 2020 Dubai later this year, where international stakeholders will discuss how to redefine education to prepare children for a post-Covid-19 world.

Speaking on the panel, Hanan Ahli, acting director general for the Federal Competitiveness and Statistics Authority in the UAE, said the digital gender gap needed to be closed.

"Collectively, we can make together a bigger impact into girls education in AI. We can all empower more young women to enter STEM fields of study and careers," she said.

"The UAE government is proactively addressing this through national strategies such as the UAE Centennial 2071, the Advanced Sciences Agenda 2031 and the UAE's Fourth Industrial Revolution strategy.

"The literacy rate of women in the UAE stands at 95.8 per cent, with a remarkable 56 per cent of the UAE's graduates in STEM courses at government universities are women."

The panellists discussed in detail how to persuade girls that coding, tech and artificial intelligence are not just the domain of white men, despite that currently being the case.

A 2020 study by the AnitaB.org Institute, which aims to advance women in technology, found that women make up only 28.8 per cent of the tech workforce, with Asian women making up just 5 per cent of that number, and Black and Hispanic women accounting for 3 per cent and 1 per cent respectively.

Only 18 per cent of girls in tertiary education around the world are pursuing STEM studies, compared to 35 per cent of boys, according to Unicef. Photo: Getty Images

Salwa Abdulla, director of the projects and programmes department at the Federal Authority for Government Human Resources, said self-empowerment was key to attracting young people into tech.

"It's not about our academic subjects that we study in schools self-learning is also an important aspect that we need to encourage," said Ms Abdulla, who has worked in tech for 18 years.

"There are a lot of open resources on the internet where we can go and just explore, learn more about AI."

In 2018, the UAE launched Madrasa, a free e-learning platform providing 5,000 videos to foster science and maths skills among Arabic-speaking students across the world.

"The platform has gained traction of over 6.5 million visitors, with 61 per cent of them being female," said Ms Ahli.

Ms John said gamification was one tool used at 01Founders to attract young men and women to code, as this helped them indirectly to build the creative and technical skills needed for a career in artificial intelligence.

Ms Abdulla agreed, and suggested teaming up with influencers in the UAE and UK.

"Social media is a great tool. Ladies are influenced by fashionistas. So we need to sponsor an AI engineer who becomes an influencer within social media," she said.

"This person needs to show people the power of AI, the power of technology, so other girls will follow."

Updated: September 8th 2021, 6:01 AM

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

Sector: transport and logistics

Size: 150+ employees

Investment: approximately $8 million

Investors include: Singapores Battery Road Digital Holdings, Egypts Algebra Ventures, Uber co-founder and former CTO Oscar Salazar

PROFILE OF HALAN

Started: November 2017

Founders: Mounir Nakhla, Ahmed Mohsen and Mohamed Aboulnaga

Based: Cairo, Egypt

See the rest here:

Coding and AI jobs: How do we get more girls into tech? - The National