Archive for the ‘Artificial Intelligence’ Category

Update on Artificial Intelligence: USPTO Urges Federal Circuit to Affirm Decision That AI Cannot Qualify as an Inventor – JD Supra

In three previous blog posts, we have discussed recent inventorship issues surrounding Artificial Intelligence (AI) and its implications for life sciences innovations focusing specifically on scientist Stephen Thalers attempt to obtain a patent for an invention created by his AI system called DABUS (Device for Autonomus Bootstrapping of Unified Sentence). Most recently, we considered Thalers appeal of the September 3, 2021 decision out of the Eastern District of Virginia, which ruled that under the Patent Act, an AI machine cannot qualify as an inventor. Continuing this series, we now consider the USPTOs recently filed opposition to Thalers appeal.

In its opposition brief, the USPTO argued that under the plain language Congress chose to incorporate in the Patent Act, only a human being can be considered an inventor. The USPTO first noted that the definitions of inventor and joint inventor under the Patent Act both unequivocally refer only to an individual or individuals. For example, inventor is defined under the Act as the individual or, if a joint invention, the individuals collectively who invented or discovered the subject matter of the invention.

While the Patent Act does not explicitly define the term individual, the USPTO argued that in other instances where the term is not explicitly defined, courts have interpreted Congresss use of the term individual in a given statute as denoting a human being, as opposed to other things. The USPTO provided the example of Mohamad v. Palestinian Auth., a 2012 case in which the Supreme Court evaluated whether Congresss use of the term individual in the Torture Victim Protection Act (TVPA) could be construed to include an organization. There, the Court quoted from several well-known dictionaries and considered the use of the term in everyday parlance, to determine that the ordinary meaning of the term individual refers only to a human being or natural person. The Court in Mohamad also referred to the Dictionary Act, 1 U.S.C. 1, which provides that the legislative use of the term individual denotes something separate and apart from non-human beings.

The USPTO argued that the Supreme Courts analysis in Mohamad is equally applicable to the Patent Act as it is to the TVPA. For example, the term individual is used in the Patent Act as a noun, just as it is in the TVPA. And, according to the USPTO, just as the Mohamad Court recognized no onerefers in normal parlance to an organization as an individual, it is equally true that no one refers in normal parlance to a machine or collection of source code as an individual. Further, the USPTO pointed out that the Dictionary Act applies not only to the TVPA, but to all congressional enactments including the Patent Act.

Though the Supreme Courts opinion in Mohamad acknowledges that Congress is free to give the term individual a broader or different meaning, such broader construction by a court requires some affirmative indication [that Congress] intended such a result. Here, the USPTO argues that Thaler has never pointed to any textual evidence that Congress intended a broader meaning for the term. The USPTO argues that Thaler has only put forth non-textual policy arguments. For example, Thaler argues that denying inventorship to AI would place the United States behind other countries [that] are promoting the progress of science, and would amount to adopt[ing] luddism. However, according to the USPTO, these policy considerations cannot overcome the plain meaning of the text.

We will continue to monitor this appeal, as it has important implications for life sciences companies employing AI technologies, particularly given the low probability that Congress will act on this issue in the short term.

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Update on Artificial Intelligence: USPTO Urges Federal Circuit to Affirm Decision That AI Cannot Qualify as an Inventor - JD Supra

6 Ways Data Science and Artificial Intelligence is Driving Innovation to Help the Environment – Analytics Insight

6 Ways Data Science and Artificial Intelligence is Driving Innovation to Help the Environment

Data science is preparing data for analysis. Artificial Intelligence (AI) is the implementation of a predictive model to forecast future events and helps computers or machines or robots controlled by computers to work as an alternative to humans.

With Data Science and AI becoming a transformative phenomenon for businesses and consumers, its vital to how it impacts the environment and embraces the challenges confronted in an increasingly populated, polluted and competitive world. The global AI and data science market is estimated to value more than $309 billion and $230 billion respectively. The technological advancements and initiatives in this field could have a significant impact on the environment.

Electric vehicles are good for the environment. They generate lesser greenhouse gases and cause less pollution. It is true even if we account for the electricity required to use them. Unmanned or automated driving, studying driver behaviour patterns, GPS navigation systems are some advancements where AI is playing a key role in the EV Industry. The implementation of AI in improving EVs, facilitating EV charging stations, and EV integration with the smart grid will encourage people to adopt electric vehicles and open a new pathway of eco-driving thus helping reduce greenhouse gas emissions.

As per research, in India more than 50 kg of food is wasted per person in a year, calculating to about 68,760,163 tonnes and is ranked at 94th position out of 107 countries. In fact, every country generates food waste at the consumer level irrespective of their income levels.

Given the pressure on already severely depleted soils to provide food for an ever-growing global population and the fact that roughly a third of food is never eaten, innovative AI technology can be used for overcoming this issue. Retailers can use AI to check and dispose of food items before they turn bad. Data analysis helps to calculate and predict the volume of food consumption in restaurants and households for them to reduce food waste eventually. Besides, AI could significantly improve packaging, increase the shelf life of food items, avoid food wastage by making a more transparent supply chain management system.

The recycling system of waste needs to be transformed urgently, as most of the waste generated over the year is mostly of single-use products. As per research in 2019, 660,787.85 tonnes of plastic waste was generated in India, out of which only 60% was recycled. One particular difficulty with recycling is the issue of segregation of waste. The use of robots that have sensors to separate different types of waste will help in a quicker and easier way of recycling as each product varies in its texture, shape and size. AI can also be used for creating an automated waste disposal system. Another way is by using image recognition technology which helps to collect information on waste and find alternative material solutions, eventually improving the recycling pattern of waste.

Sewage pollution is yet another concern, especially here in India. The major cause of increasing sewage pollution is that most of the problems go undetected. However, the use of pattern recognition, an AI technique, would help to monitor and track the wastewater flow. Besides, algorithms can detect patterns and create critical data for research and analysis for future improvements.

Over the years, the population of wildlife species has been continuously depleting. AI and data science help environmentalists to study the movement of animals and other species, their behaviour, the routes they follow their reproduction and hunting patterns. It helps curtail poaching and is an effective way of surveillance, for instance by using drones with cameras. Currently, there are environmental, sustainability projects taking place using AI and data science, to prevent forest fires and monitor wildlife. It also helps the environmentalists to monitor rare wildlife species populations and track them on cameras with smart sensors.

AI and data science can in the coming future be applied to thousands of issues affecting the environment. Data from various Space Research Centres can be used with help of AI technology to identify and monitor changes in land and sea areas, ice caps etc. Besides, data analysis can be done to reduce pollution and help fight Climate Change.

These technological solutions using AI and data science could help solve some of the most difficult environmental challenges.

Dr.MukeshKwatra,Founder of Smiling Tree

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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6 Ways Data Science and Artificial Intelligence is Driving Innovation to Help the Environment - Analytics Insight

Dedalus and Ibex announce a strategic partnership to bring the power of artificial intelligence to digital pathology – PR Newswire

MILAN, March 10, 2022 /PRNewswire/ --Dedalus Group("Dedalus"), the leading healthcare and diagnostic software solutions provider in Europe, and Ibex Medical Analytics("Ibex"), the market leader in artificial intelligence (AI)-powered cancer diagnostics, today announced a strategic partnership to bring the power of artificial intelligence to digital pathology.

The partnership will bring the power of Ibex's clinical-grade AI algorithms into Dedalus' end-to-end digital pathology solution. This will benefit pathologists and patients through enhanced quality of diagnosis, at speed.

The increasing demand for pathology services posed by the growing number of cancer patients and global shortage of trained pathologists, leads pathology laboratories to actively seek efficiency-enhancing solutions that enable them to maintain high accuracy levels and reduce time to diagnosis.

Dedalus' end-to-end digital pathology solution addresses the needs of anatomic pathology labs and ensures interoperability with existing multi-vendor solutions, enabling a seamless, gradual evolution towards full digitization to meet the increasing demands of the healthcare system.

With over 30 years' experience in laboratory solutions, Dedalus has deployments in over 5700 laboratories globally, and has been instrumental in successfully bringing cutting-edge technologies into the laboratories to make the systems as agile, efficient, and accurate as possible.

Ibex transforms cancer diagnosis by harnessing AI and machine learning technologies at an unprecedented scale. The company's Galen platform has demonstrated outstanding outcomes in multiple clinical studies on various tissue types and clinical workflows. It is deployed in labs worldwide where it is used as part of everyday clinical practice.

Ibex's clinical-grade AI algorithms will seamlessly integrate into Dedalus end-to end digital pathology solution, enabling smooth workflows from a single application. The joint solution will analyse cases prior to human pathologists' review, providing decision support tools that will enable increased focus on cancerous slides and areas of interest, streamline reporting, improve laboratory efficiency, and increase diagnostic confidence.

"Dedalus is the leading healthcare and diagnostic software provider in Europe. As part of our commitment to accelerate the digital transformation in healthcare, we strongly believe in the value of artificial intelligence, specifically in pathology and cancer diagnoses. Therefore, we are proud to partner with Ibex Medical Analytics, which is a global leader in AI-powered solutions for pathology labs and cancer diagnostics," said Marlen Suller, Head of In Vitro Diagnostics Business Unit at Dedalus.

"Our AI solutions transform pathology and help physicians around the world provide on-time, quality diagnosis to patients," said Joseph Mossel, CEO and Co-founder of Ibex Medical Analytics. "Yet to unlock the full potential of artificial intelligence, pathologists and health systems need AI-enabled workflows and integrated cancer pathways. We are excited to partner with market leaders Dedalus and to deliver end-to-end diagnostic modalities that improve the way laboratories work and support better cancer care."

ABOUT DEDALUS

Dedalus Group is the leading healthcare and diagnostic software provider in Europe, supporting the digital transformation of 6300 hospitals and 5700 Laboratories worldwide, processing its solutions for more than 540 millions of population worldwide. Dedalus supports the whole continuum of care, offering open standards-based solutions serving each actor of the Healthcare Ecosystem to provide better care in a healthier planet.

For more information, visitwww.dedalus.com

ABOUT IBEX MEDICAL ANALYTICS

Ibex pioneers AI-powered cancer diagnostics in pathology. We empower physicians to provide every patient with an accurate, timely and personalized cancer diagnosis by developing clinical-grade AI algorithms and digital workflows that help detect and grade cancer in biopsies. Our Galen platform is the first-ever AI-powered integrated diagnostics solution in pathology and used in routine clinical practice worldwide, supporting pathologists and providers in improving the quality and accuracy of diagnosis, implementing comprehensive quality control, reducing turnaround times and boosting productivity with more efficient workflows.

For more information, visitwww.ibex-ai.com

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Dedalus and Ibex announce a strategic partnership to bring the power of artificial intelligence to digital pathology - PR Newswire

Artificial intelligence innovation among power industry companies has dropped off in the last year – Power Technology

Research and innovation in artificial intelligence (AI) in the power industry operations and technologies sector has declined in the last year. The most recent figures show that the number of AI-related patent applications in the industry stood at 84 in the three months ending January down from 191 over the same period in 2020.

Figures for patent grants related to AI followed a similar pattern to filings shrinking from 64 in the three months ending January 2020 to 10 in the same period in 2021.

The figures are compiled by GlobalData, which tracks patent filings and grants from official offices around the world. Using textual analysis, as well as official patent classifications, these patents are grouped into key thematic areas, and linked to key companies across various industries.

AI is one of the key areas tracked by GlobalData. It has been identified as being a key disruptive force facing companies in the coming years, and is one of the areas that companies investing resources in now are expected to reap rewards from.The figures also provide an insight into the largest innovators in the sector.

Siemens was the top AI innovator in the power industry operations and technologies sector in the latest quarter. The company, which has its headquarters in Germany, filed 51 AI-related patents in the three months ending January. That was down from 125 over the same period in 2020.

It was followed by the US-based Honeywell International with 21 AI patent applications, South Korea-based Korea Electric Power (19 applications), and the US-based 3M (10 applications).

Korea Electric Power has recently ramped up R&D in AI. It saw growth of 68.4% in related patent applications in the three months ending January compared to the same period in 2020 the highest percentage growth out of all companies tracked, with more than 10 quarterly patents in the power industry operations and technologies sector.

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Artificial intelligence innovation among power industry companies has dropped off in the last year - Power Technology

1 Artificial Intelligence Growth Stock to Buy Now and Hold for the Long Term – The Motley Fool

Artificial intelligence (AI) promises to be one of the most transformative technologies of our time. It has already proven it can reliably complete complex tasks almost instantaneously, eliminating the need for days or even weeks of human input in many cases.

The challenge for companies developing this advanced technology is building a business model that can deliver it efficiently since AI is a brand-new industry with little existing precedent. That's what makes C3.ai ( AI 7.11% ) a trailblazer, as it's the first platform AI provider helping companies in almost any industry access the technology's benefits.

C3.ai just reported its fiscal 2022 third-quarter earnings result, and it revealed continued growth across key metrics, further cementing the case for owning its stock for the long run.

Image source: Getty Images.

As more of the economy transitions into the digital realm, a growing number of companies will find themselves with access to game-changing tech like artificial intelligence. In the second quarter of fiscal 2022, C3.ai said it was serving 14 different industries, double the amount from the corresponding quarter in the previous year. It indicates that more sectors are already proactively seeking the benefits of AI.

One of those sectors is oil and gas, which represents the largest portion of C3.ai's total revenue. The company has a long-standing partnership with oil giant Baker Hughes. Together, the two companies have developed a suite of AI applications to predict critical equipment failures and reduce carbon emissions in drilling and production operations.

Shellis a core customer of these applications, and it's using them to monitor 10,000 devices and 23 large-scale oil assets, with the technology processing 1.3 trillion predictions per month.

In the recent Q3 of fiscal 2022, C3.ai revealed a new partnership with the U.S. Department of Defense worth $500 million over the next five years. It's designed to accelerate the adoption of AI applications across the defense segment of the federal government.

But some of C3.ai's most impressive partnerships are those with tech behemoths like Microsoft and Alphabet's Google. They're collaborating with C3.ai to deploy AI applications in the cloud to better serve their customers in manufacturing, healthcare, and financial services, among other industries.

From the moment a potential customer engages C3.ai, it can take up to six months to deploy their AI application. Therefore, it's important to watch the company's customer count as it can be a leading indicator for revenue growth in the future.

In fiscal Q3 2022, C3.ai reported having 218 customers, which was an 81% jump over Q3 2021. Over the same period, remaining performance obligations (which are expected to convert to revenue in the future) climbed by 90% to $469 million.

Since quarterly revenue grew a more modest 42% in the same time span, both of the above metrics hint at a potential revenue-growth acceleration over the next few years. The company has also raised its sales guidance twice so far in the first nine months of fiscal 2022, albeit by just 2% in total, now estimating $252 million in full-year revenue.

C3.ai has been a publicly traded company for a little over a year, listing in December 2020. It quickly rallied to its all-time high stock price of $161 before enduring a painful 87% decline to the $20 it trades at today. The company hasn't grown as quickly as investors anticipated, and it also hasn't achieved profitability yet.

But right now, C3.ai trades at a market valuation of $2.1 billion, and it has over $1 billion in cash and short-term investments on its balance sheet. Put simply, investors are only attributing a value of around $1 billion to its AI business despite over $250 million in revenue expected by the close of fiscal 2022 and a portfolio of A-list customers.

Moreover, C3.ai has a gross profit margin of 80%, affording it plenty of optionality when it comes to managing expenses. This places it in a great position to eventually deliver positive earnings per share to investors once it achieves a sufficient level of scale.

While C3.ai stock carries some risk, especially in the middle of the current tech sell-off, by many accounts it's beginning to look like an attractive long-term bet. Advanced technologies like AI will only grow in demand over time, and this company is a great way to play that trend.

This article represents the opinion of the writer, who may disagree with the official recommendation position of a Motley Fool premium advisory service. Were motley! Questioning an investing thesis even one of our own helps us all think critically about investing and make decisions that help us become smarter, happier, and richer.

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