Category Archives: Artificial Intelligence

The ramifications of advances in artificial intelligence (A.I.) are being felt further afield than anyone expected. A.I. perhaps entered the public consciousness in the 1990s thanks to chess competitions, but it's now infiltrating art competitions and, soon, the written word. Some commercial offerings can provide paragraphs of text based on brief prompts, keywords, and tone parameters. Users of Google's email service have, of course, been microdosing on A.I. since 2018, when Gmail rolled out Smart Compose.

What these developments bring home is that people in the so-called "creative class" are now facing the first-person reckoning that automation has long presented to blue-collar workers: Technology is going to radically change the way we work.

As an analyst at a think tank, my job consists of processing policy trends, formulating new ideas to tackle economic and social problems, and advancing them through the written word. If programs like Midjourney, DALL-E, and Voyager can already captivate human audiences, I haven't the slightest doubt that my modest ability to metabolize the policy landscape, reason my way to novel solutions, and manipulate language in provocative, engaging ways will soon be matchedand then surpassedby A.I. programs designed for the task.

While I am under no illusion that my work merits any blue ribbons, putting thoughts into words that persuade or stir emotion entails a certain artistry. It's an engrossing and gratifying process, one from which I derive identity. When I contemplate that a computer could soon do it better, I, like the Lancashire handloom weavers of the early 19th century, feel more than a bit threatened.

Garry Kasparov dealt with this conundrum two decades ago and has had a head start in managing the prospect of obsolescence. Kasparov, an all-time great chess player, had the distinction of holding the world title just at the same moment that computer chess programs ramped up their prowess. In 1996, Kasparov beat what was then the strongest chess engine ever created, IBM's Deep Blue. But as he recounts in his memoir, Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins, he knew then that his reign would soon end. Indeed, in a 1997 rematch for which Kasparov was handsomely compensated, an updated Deep Blue brought the age of A.I. to global attention, dealing the champion a stunning defeat in the match's decisive sixth game.

In Deep Thinking, published in 2017, Kasparov explains how his perspective on A.I. has evolved and why. Despite the anguish the 1997 loss caused him, he views A.I. as one of the greatest opportunities for humanity to advance its well-being. The reason is that Kasparov has observed in the intervening years that the highest level of performance, on the chessboard and elsewhere, is reached when humans work with smart machines.

After Deep Blue's programmers established that it could see deeper into the game than the human mind, Kasparov and a group of partners came up with a new concept: What if instead of human vs. machine, people played against one another but with the assistance of chess software?

They called the new style of play "advanced chess," and the outcomes surprised Kasparov. It wasn't the player with the best chess software that necessarily won, nor was it the best human player. Rather, the top performers were the players who were able to use the machines most effectively, those who were able to get the most out of the chess engines and their own creative abilities.

Operating on the premise of Moravec's Paradox, i.e., where machines are strong is where humans are weak and vice versa, what Kasparov took away from the advanced chess experiment is that a clever working process beats both superior human talent and superior technological horsepower.

The same insight can be leveraged by artists, composers, writers, designers, and the like. Rather than viewing A.I. as the end of our livelihoods, we ought to see the opportunities it presents for better work.

For the creative class, the answer to the A.I. challenge is to make the most of the programs available to us. Is artistry lost because of A.I., or is it unlocked, as we are freed from some of the more formulaic structuring processes that drain energy? By delegating these aspects of creation to A.I., I anticipate having more mental space available to generate the rhetorical flourishes and the witty bits of embroidery that make writing enjoyable.

Yes, people deploying A.I. in the writing world, art competitions, and elsewhere will likely face scorn. But while a level playing field is appropriate in defined competitions, in open-ended fields to accuse a rival of cheating would be no more meaningful than in that of the textile industry. For the intrepid writer, A.I. will create opportunities to produce better work at a faster clip, just as the power loom did for the weavers of Lancashire.

Rather than fear, and certainly rather than Luddite suppression, this ought to be a moment of optimism. A.I. is coming for our jobs. Its arrival, however, will not be a harbinger of obsolescence but a catalyst for greater achievement.

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Artificial Intelligence Will Change JobsFor the Better - Reason

Corruption Perception Index (CPI) by Transparency International is the most widely used corruption index. And ironically, India has been constantly ranking only a few notches above the underdeveloped African countries. Corruption hinders the economic growth of a country preventing it from progressing in the right direction. Perhaps the legal procedure and laws have a narrow application for a diverse concept like corruption. Many a time it is highly impossible to differentiate between the so-called welfare measure from the very personal political agenda of the leaders. While financial and banking systems have been put under the scanner for corruption and fraudulent actors by global agencies like the world bank and IMF, corruption in other sectors is more than difficult to identify if not prevent. The organizational infrastructure cannot support the analysis of a vast amount of data and sift through it to connect the dots between different events to find malpractice.

Off late artificial intelligence is proving to be a savior of anti-corruption agencies world over. AI and machine learning, given that they can identify patterns in the data when applied to analyze inputs from different data points, could identify kinks from the mele of complex transactions. Automating public record searches can detect activities of corruption such as Money laundering, tax evasion, suspicious tenders, or bids in public procurements efficiently. However, until a few issues such as biased algorithms and data inadequacy are addressed, AIs automated systems cannot be set free in the open to catch the thief, in spite of the benefits like objectivity, efficiency and the cost-savings it offers.

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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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The Artificial Intelligence Pill for A World Vexed with Corruption - Analytics Insight

Chipotle's Chippy, an autonomous kitchen assistant that integrates culinary traditions with ... [+] artificial intelligence to make tortilla chips, is moving into the next phase of testing and will be integrated in a restaurant next month.

During Chipotles Q2 earnings call in late July, executives made it clear the system needed to refine some of its operational processes as dine-in business returns while off-premise business remains elevated.

In doing so, Chief Restaurant Officer Scott Boatwright touted the companys Project Square One, a game plan focused on employee training to execute orders more efficiently. Today, the company announced its also getting more technology involved.

Chipotle is testing two technologies specifically to streamline operations and reduce frictiona kitchen management system and an advanced location-based platform.

In eight Southern California restaurants, Chipotle is testing PreciTastes kitchen management system that provides demand-based cooking and ingredient preparation forecasts by leveraging artificial intelligence and machine learning. According to Chipotle, the system monitors ingredient levels in real time and notifies employees how much to prep, cook and when to start cooking. The system was created to not only optimize throughput but to also minimize food waste.

The new kitchen management system has alleviated manual tasks for our crew and given restaurant managers the tools they need to make informed in-the-moment decisions, ultimately enabling them to focus on an exceptional culinary and an outstanding guest experience, Chief Technology Officer Curt Garner said in a statement.

This isnt Chipotles first foray into AI. Earlier this year, Chipotle announced a test with Miso Robotics to bring its artificial intelligence-driven Chippy into its Cultivate [innovation] Center to replicate the chains signature tortilla chips. That test is now expanding, with Chippy making its first restaurant debut next month in a Fountain Valley, California, location.

From there, the company will gauge employee and guest feedback before developing a broader rollout plan.

During a recent interview, Garner said the company is looking at everything from internet of things to machine learning to run its restaurants more efficiently and enable crew members to focus on other tasks.

When you see us leaning into this space, it will be a question of are there better tools to help our crews versus removing a task? Those are the kind of things were looking at, Turner said.

The company is also currently testing Radius Networks Flybuy, a contextual restaurant program, at 73 Cleveland-area restaurants designed to identify Chipotle app users intent upon arrival. The location-based technology utilizes real-time data to let customers know their orders are ready, to remind them to scan the Chipotle Rewards QR code at checkout and more. It even alerts customers if theyre in the wrong pick-up location.

The program has yielded positive results so far, according to Chipotle, including improved in-store rewards engagement and delivery efficiencies.

Empowering our restaurants with advanced technologies is critical for operational excellence and better positions our teams for our ambitious growth plans, Boatright said in a statement.

Notably, Chipotle isnt the only chain exploring AI technology to improve operations. White Castle has been testing Miso Technologys Flippy in the back of the house for about two years, for instance, while Jamba has partnered with autonomous food platform Blendid to automate smoothies. Several restaurant chains, including Applebees, IHOP and Tropical Smoothie Cafe, leverage Flybuy.

In fact, a new survey from Capterra found that 76% of restaurants are currently using automation in three or more areas of operation, while 96% of restaurants are using some type of automation tool in the back of the house. As such, the cooking robotics space is expected to grow by over 16% a year through 2028 with an estimated worth of $322 million by 2028.

That said, Chipotles scale, company-owned model and zero-debt balance sheet adds a bit more intrigue to this trend. Chipotle has some latitude to pilot new solutions without franchisee investment or pushback, and any proven return on investment will likely provide a strong case for adoption across an industry still very much struggling with labor shortages.

Further, all of these technologies enhance throughput, a major focus for Chipotle to drive more sales. During the companys Q2 call, for example, CEO Brian Niccol said order fulfilment was in the low 30s on a per-15-minute basis nearly 10 years ago, which adds a full percent on comp sales on the day.

On a 15-minute basis, thats what were going after, he said during the earnings call.

Chipotles announcements today come on the heels of the companys Cultivate Next venture fund launch, created to identify strategically aligned companies for early-stage investments. As part of this $50 million fund, Chipotle has already invested in Hyphen, a foodservice platform that automates kitchen operations, and Meati Foods, a company that provides plant-based proteins.

Chipotle is also leveraging a new scheduling tool, has invested in autonomous delivery company, Nuro, and is testing radio-frequency identification to trace and track ingredients in its restaurants.

In a recent statement, Garner said the company is exploring investments in innovations that will enhance employee and guest experience and quite possibly revolutionize the restaurant industry.

Investing in forward-thinking ventures that are looking to drive meaningful change at scale will help accelerate Chipotles aggressive growth plans, he said.

Chipotle currently has about 3,000 locations, with plans to grow to about 7,000 in the coming years.

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Chipotle Is Testing More Artificial Intelligence Solutions To Improve Operations - Forbes

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in Accounting Market Research Report by Component (Services and Solutions), Technology, Deployment, Application, Region (Americas, Asia-Pacific, and Europe, Middle East & Africa) - Global Forecast to 2027 - Cumulative Impact of COVID-19" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence in Accounting Market size was estimated at USD 1,556.52 million in 2021, USD 2,074.02 million in 2022, and is projected to grow at a CAGR 33.42% to reach USD 8,781.42 million by 2027.

Competitive Strategic Window:

The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies to help the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. It describes the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth during a forecast period.

FPNV Positioning Matrix:

The FPNV Positioning Matrix evaluates and categorizes the vendors in the Artificial Intelligence in Accounting Market based on Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Market Share Analysis:

The Market Share Analysis offers the analysis of vendors considering their contribution to the overall market. It provides the idea of its revenue generation into the overall market compared to other vendors in the space. It provides insights into how vendors are performing in terms of revenue generation and customer base compared to others. Knowing market share offers an idea of the size and competitiveness of the vendors for the base year. It reveals the market characteristics in terms of accumulation, fragmentation, dominance, and amalgamation traits.

The report provides insights on the following pointers:

1. Market Penetration: Provides comprehensive information on the market offered by the key players

2. Market Development: Provides in-depth information about lucrative emerging markets and analyze penetration across mature segments of the markets

3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments

4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players

5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments

The report answers questions such as:

1. What is the market size and forecast of the Global Artificial Intelligence in Accounting Market?

2. What are the inhibiting factors and impact of COVID-19 shaping the Global Artificial Intelligence in Accounting Market during the forecast period?

3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Artificial Intelligence in Accounting Market?

4. What is the competitive strategic window for opportunities in the Global Artificial Intelligence in Accounting Market?

5. What are the technology trends and regulatory frameworks in the Global Artificial Intelligence in Accounting Market?

6. What is the market share of the leading vendors in the Global Artificial Intelligence in Accounting Market?

7. What modes and strategic moves are considered suitable for entering the Global Artificial Intelligence in Accounting Market?

Market Dynamics

Drivers

Restraints

Opportunities

Challenges

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/s6uz84

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Insights on the Artificial Intelligence in Accounting Global Market to 2027 - Rising Demand for Intelligent Accounting Processes Presents...

Journalists are automating processes and using systems that mimic human behavior to design tasks related to news gathering, content creation, distribution, marketing, and subscriptions in Latin America.

FREMONT, CA: Artificial intelligence (AI) has stopped merely being a science fiction component and has become a reality in recent years. Automation of processes and the creation of systems that mimic human behavior have reached journalism and are being used to design tasks of news gathering, content creation, distribution, marketing, and subscriptions. Automating processes and creating systems that mimic human behavior have reached journalism.

The use of AI is currently somewhat limited, despite its enormous potential, and the region is ravenous for information regarding the subject.

Insufficient funds and a need for training

The organization needs AI training in addition to producing articles for publication in Latin American media.

Ironically, although there is a great deal of understanding of the potential benefits of AI systems in the media, very little or even nothing has been done at the organizational level to implement these systems.

There is an unmistakable desire present in newsrooms to implement AI. The majority of the newsrooms had not taken advantage of the chance to implement AI into their day-to-day operations, despite its availability. The typical reaction was either a lack of resources or an absence of a corporate vision to adopt AI technologies as an integral part of the organization's future. Both of these issues were cited as the reason for the failure.

Similarly, the request made by journalists was to obtain training and trade experiences with other forms of media. The region is willing to enter the field of AI, but it needs basic information about the currently available prospects.

User loyalty

It would appear that the holy grail of reader monetization is the application of algorithms to make sense of data. Many news organizations in Latin America are either actively investigating this topic or are eager to do so. Particularly in the case of television networks, which are not accustomed to working with this kind of instrument.

The media are utilizing machine learning and AI to gain a deeper understanding of specific consumer habits, user loyalty, and the integration of advertising campaigns.

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Reasons behind the Limited Use of Artificial Intelligence in Latin American Media - CIOReview

Visiongain has published a new report entitled the Artificial Intelligence (AI) in Drug Discovery 2022-2032. It includes profiles of Artificial Intelligence (AI) in Drug Discovery and Forecasts Market Segment by Offering, (AI Software, AI Services) Market Segment by Technology, (Deep Learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning, Other Technology) Market Segment by Applications, (Oncology, Infectious Diseases, Neurological Disorders, Metabolic Diseases, Cardiovascular Diseases, Other Applications) Market Segment by Type, (Target Identification, Molecule Screening, Drug Design and Drug Optimization, Preclinical and Clinical Testing) PLUS COVID-19 Impact Analysis and Recovery Pattern Analysis (V-shaped, W-shaped, U-shaped, L-shaped) Profiles of Leading Companies, Region and Country.

The global artificial intelligence (AI) in drug discovery market was valued at US$791 million in 2021 and is projected to grow at a CAGR of 30.7% during the forecast period 2022-2032.

In a Pharmacological Screen, AI Has a Stronger Prediction Power for Defining Relevant Interactions

AI makes use of the most recent developments in biology and computation to create cutting-edge drug discovery algorithms. AI has the potential to level the playing field in drug research, with to rapid increases in computing capacity and lower processing costs. In a pharmacological screen, AI has a stronger prediction power for defining relevant interactions. As a result, by carefully choosing the assay parameters in question, the risk of false positives can be decreased. Most crucially, AI has the ability to shift drug screening from the bench to a virtual lab, where results can be produced more quickly and intriguing targets can be prioritised without requiring extensive experimental input or personnel hours.

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Artificial Intelligence (AI) in Drug Discovery Market Report 2022-2032

How has COVID-19 had a significant negative impact on the Artificial Intelligence (AI) in Drug Discovery Market?

The COVID-19 pandemic presented a significant challenge to the pharmaceutical and bioanalytical communities in the creation of vaccines and therapies, as well as ongoing drug development activities. Existing procedures were tested to cope with reduced personnel at facilities and increased workloads for COVID-19-related study assistance, which included preclinical testing, clinical trial initiation, bioanalysis, and interactions with regulatory bodies, all in ultra-short timelines. Creative reimagining of procedures and the removal of barriers some of which had previously been regarded immovable were major factors in the project's success. Pharmaceutical firms working on antiviral medicines or vaccines have to deal with pandemic-related problems and alter their strategies in order to continue enrolling patients in existing clinical studies and developing new treatments and cures. The remainder of this essay focuses on bioanalysis and drug development issues and lessons learned.

How this Report Will Benefit you?

Visiongains 483 page report provides 270 tables and 264 charts/graphs. Our new study is suitable for anyone requiring commercial, in-depth analyses for the global artificial intelligence (AI) in drug discovery market, along with detailed segment analysis in the market. Our new study will help you evaluate the overall global and regional market for Artificial Intelligence (AI) in Drug Discovery. Get the financial analysis of the overall market and different segments including type, technology, application, offering and capture higher market share. We believe that high opportunity remains in this fast-growing artificial intelligence (AI) in drug discovery market. See how to use the existing and upcoming opportunities in this market to gain revenue benefits in the near future. Moreover, the report would help you to improve your strategic decision-making, allowing you to frame growth strategies, reinforce the analysis of other market players, and maximise the productivity of the company.

What are the current market drivers?

AI Utilizes the Latest Advances in Biology and Computing to Develop State-of-the-Art Algorithms for Drug Discovery

With the introduction of artificial intelligence (AI) and machine learning, the pharmaceutical business is undergoing a significant transformation. While many see this new technology as a potential threat, it could actually be the solution to our persistent prescription shortages. Indeed, AI has already proven to be useful in several aspects of drug discovery and development, from assisting scientists in finding new potential treatments to forecasting which pharmaceuticals will fail clinical trials. There's no doubt that these technologies will have a huge impact on the future of medicine as more pharma companies adopt them.

Thanks to AI, the Cost and Timelines of Developing a New Treatment Will Be Rewritten

The cost of discovering a new medicine is estimated to be in the billions of dollars. A huge percentage of the money invested on the nine out of ten proposed new therapy discoveries that fail somewhere between clinical trial phase I and regulatory approval goes down the drain. Surprisingly, few in the industry doubt the value of doing things differently. Many prominent pharma companies believe that the answer is within grasp when assisted by cutting-edge technology. Using the supercomputer IBM Watson, Pfizer uses machine learning (ML) or deep learning (DL) and breakthroughs to develop immuno-oncology medications.

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Artificial Intelligence (AI) in Drug Discovery Market Report 2022-2032

Where are the market opportunities?

A New Wave of Drug Discovery is Setting the Ideal for the World

Small-molecule drug discovery can benefit from AI in four ways: new biology, improved or original chemistry, higher success rates, and faster and cheaper discovery processes. Many issues and limits in traditional R&D can be addressed with this technique. Each tool provides drug research teams with new insights and, in some circumstances, can completely transform long-standing operations. Understanding and distinguishing between use cases is crucial because these technologies are applicable to a number of discovery scenarios and biological targets.

AI Has Received a Lot of Attention in the Pharmaceutical Business for Medication Discovery and Development

Within the pharmaceutical industry, there has been considerable focus on AI for drug discovery and development. The "AI for Drug Discovery" business includes research organisations, AI innovators both early-stage and well-funded biotech companies, and multinational pharma giants. Though artificial intelligence (AI) has only recently gained traction in the industry, computational methods to drug development particularly in chemistry and biology have a long history that predates electronic computing.

Competitive Landscape

The major players operating in the artificial intelligence (AI) in drug discovery market are Atomwise, Benevolent AI, Berg Health, Bioage, Biosymetrics, Cloud Pharmaceuticals, Cyclica, Deep Genomics, DeepMind, Envisagenics, Euretos, Exscientia, GNS Healthcare, IBM Corporation, Insilico Medicine, These major players operating in this market have adopted various strategies comprising M&A, investment in R&D, collaborations, partnerships, regional business expansion, and new product launch.

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Global Artificial Intelligence (AI) in Drug Discovery market is projected to grow at a CAGR of 30.7% By 2032: Visiongain Reports Ltd - GlobeNewswire

Artificial Intelligence (AI) is having an increasing presence in our everyday lives, and this is believed to be only the beginning. For this to continue, however, it must be ensured that AI is trustworthy in all scenarios. To assist in this endeavour, Linkping University (LiU) is co-ordinating TAILOR, an EU project that has developed a research-based roadmap intended to guide research funding bodies and decision-makers towards the trustworthy AI of the future. TAILOR is an abbreviation of Foundations of Trustworthy AI integrating, learning, optimisation, and reasoning.

Funded by EU Horizon 2020, TAILOR is one of six research projects created to develop the AI of the future. TAILOR is drawing up the foundation of trustworthy AI, by producing a framework, guidelines, and a specification of the needs of the AI research community.

The roadmap presented by the project is the first step on the way to standardisation, where decision-makers and research funding bodies can gain an understanding of the development of trustworthy AI. Research problems must be solved, however, before this can be achieved.

Fredrik Heintz, Professor of Artificial Intelligence at LiU, and co-ordinator of the TAILOR project, emphasised the importance of trustworthy AI, explaining: The development of Artificial Intelligence is in its infancy. When we look back at what we are doing today in 50 years, we will find it pretty primitive. In other words, most of the field remains to be discovered. Thats why its important to lay the foundation of trustworthy AI now.

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Three criteria for trustworthy AI have been defined by the researchers: it must satisfy several ethical concerns, it must conform to laws, and its implementation must be robust and safe. These criteria pose challenges, however, especially the implantation of ethical principles.

Heintz explained: Take justice, for example. Does this mean an equal distribution of resources or that all actors receive the resources needed to bring them all to the same level? We are facing major long-term questions, and it will take time before they are answered. Remember the definition of justice has been debated by philosophers and scholars for hundreds of years.

Large comprehensive questions will be the projects central focus and standards will be developed for all those who work with AI. However, Heintz believes that this can only be achieved if basic research into AI is a top priority.

People often regard AI as a technology issue, but whats really important is whether we gain societal benefit from it. If we are to obtain AI that can be trusted and that functions well in society, we must make sure that it is centred on people, said Heintz.

Several legal proposals written within the EU and its Member States are written by legal specialists, but it is believed that they lack expert knowledge within AI a serious problem according to Heintz.

Legislation and standards must be based on knowledge. This is where we researchers can contribute, providing information about the current forefront of research, and making well-grounded decisions possible. Its important that experts have the opportunity to influence questions of this type.

The complete roadmap is available at Strategic Research and Innovation Roadmap of trustworthy AI.

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The importance of trustworthy Artificial Intelligence - Innovation News Network

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Explainable artificial intelligence (XAI) detects wildfire occurrence in the Mediterranean countries of Southern Europe | Scientific Reports -...

On September 22, 2022, the U.S. Patent and Trademark Office (USPTO) conducted a live meeting for its Artificial Intelligence (AI) and Emerging Technologies (ET) Partnership Series. During this meeting, panelists from industry and the USPTO provided helpful tips on drafting and prosecuting patent applications that include AI components, including special tips for the biotech industry.Key takeaways from the meeting and published materials will be summarized in our Three-Part Blog Series.

Part One Helpful Tips for Prosecuting Patents in the Biotechnology Space

Major innovations created in the biotechnology space may encounter issues in identifying patent eligible subject matter during patent prosecution (for example, panelists explained that abstract idea and natural phenomenon-based rejections are relatively common in the art unit for Biotechnology and Organic fields). In one key takeaway, the panel suggested drafting an application with specific details about the innovation in order to support patent eligibility and enablement for the innovative concept.

Other helpful tips from the panel discussion included:

Moderator Charles Boudreau (a Lead Administrative Patent Judge at the USPTO) also walked the panelists through the use of common terms to help improve the examiners search for prior art and potentially help PTAB or District Court judges improve their understanding of the technology.

See the article here:

Takeaways From the U.S. Patent and Trademark Offices Artificial Intelligence and Emerging Technologies Partnership Series Part One of Three - JD...

MadameNoire Featured Video

Source: Courtesy of Parfait / Parfait

Wigs are a huge part of the Black hair experience. Many Black women opt to wear wigs that will not only give them a go-to protective style but also have them serving different looks for every occasion. Though its convenient, many Black women, like me, are resistant to entering into the wig world. Between the high prices, installation process and maintenance, it just seems like a headache. But four Black women are determined to change our minds with Parfait, an online company that uses artificial intelligence to make gorgeous custom wigs.

Parfait is the brainchild of 31-year-old CEO Isoken Igbinedion. The idea was conceived after she went to Afrotech in 2019 and noticing the absence of technology that serves Black women. Once she came up with the idea for Parfait, she summoned her University of Pennsylvanias Wharton School classmate 31-year-old Simone Kendle, her younger sister 29-year-old Ifueko Igbinedion, who attended Stanford University and MIT and Marlyse Reeves, 27, who also attended MIT. All four women have impressive backgrounds in the tech world. They have previously worked for Amazon, Microsoft, Capital One, Google, IBM, Waymo and NASA. They combined their expertise and in 2022, Parfait was brought to life.

All it takes is four selfies for Parfait to bring your dream wig to life. First, customers schedule a virtual consultation with a master hair stylist to discuss wig ideas. Then, with those four selfies, the artificial intelligence can calculate the size of your head so that the wig cap fits perfectly. It also helps pick the best hues for the customers skin tone. The customized wig then arrives in five to seven business days.

The wigs are made with raw hair and they come pre-tinted, pre-plucked and pre-cut. They all come with HD lace and closures. The wig cap is also breathable so you can scratch your own scalp as needed. The hair can be manipulated any way youd like. The hair is heat-friendly so the curly wigs can be straightened. They can also be colored and have a life span of two years. If the customer is dissatisfied, they can return it free of charge. Master stylists are available for as long as the customer owns the wig.

With the use of artificial intelligence you may think that hairstylists are being pushed out of the hair industry. Igbinedion said this technology cant exist without them. Parfait actually employs hairstylists and they play a crucial role in the customization of the wig. When technology falls short, the hair stylists are there to fill the void. When the ladies began building the algorithms from scratch, hair stylists helped with how they built those algorithms to ensure accuracy.

Its the creativity of stylists that really make a lot of this possible, she said. Which is why were trying to build the technology to really support them in the future.

Simone Kendle, co-founder and chief marketing officer, said that their goal is to revolutionize the process of creating wigs by eliminating sweatshops and unethical practices with the use of technology.

Our long term vision is to actually innovate the manufacturing process for wigs because right now, theres no machine that can make all this and there should be, she said. The reason why these wigs are so expensive is because theres no machines, theres terrible ethical practices and labor practices overseas because its very lucrative business. But its because theres no innovation, theres no technology, theres nothing. And so were bringing all of that to the industry.

Wigs have different lengths, come in different types of hair and curl patterns. Sometimes people have a vision in mind and arent sure of how to describe what they want. Parfaits mission is to alleviate the hassle of picking the right wig.

We just want to give you guys a very personalized customer experience where you dont have to do a lot of the work to educate yourself to be able to make these products look good for you, Igbinedion said.

For their first ever celebrity collaboration, they tapped Justine Skye for her own signature capsule collection. Her line offers four different wigs: a 30-inch jet black wig, a lightly waved blonde wig, a chocolate brown 30-inch wig and a shoulder-length bob.

What struck her the most about the new startup was how innovative their process is.

Theres so many other hair companies, but theres nothing like this, she said. [They are] reinventing the way we as women, Black women, think about the concept of wigs.

Source: Courtesy of Parfait / Parfait

The What a Lie singer said that Parfait turned her into more of a wig enthusiast as well.

Its a lot easier than I thought, she added. A lot more convenient than I thought too. For me, either my hair in braids or I just flick it back. And so these these units, they give me the flexibility to just be whoever I want to be.

Learn more about the Parfait experience here.

RELATED CONTENT:She Tried It: Do Wigs With Clear Lace Live Up To The Hype?

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Parfait Is Here To Revoluntionize The Wig World With Artificial Intelligence - MadameNoire