Category Archives: Artificial Intelligence

DUBLIN, March 19, 2021 /PRNewswire/ -- The "Artificial Intelligence in Supply Chain Management Market by Technology, Processes, Solutions, Management Function (Automation, Planning and Logistics, Inventory, Risk), Deployment Model, Business Type and Industry Verticals 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This report 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 report 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 report 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 report 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.

Select Report Findings:

Modern supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer. Supply Chain Management (SCM) solutions are typically manifest in software architecture and systems that facilitate the flow of information among different functions within and between enterprise organizations.

Leading SCM solutions catalyze information sharing across organizational units and geographical locations, enabling decision-makers to have an enterprise-wide view of the information needed in a timely, reliable and consistent fashion. Various forms of Artificial Intelligence (AI) are being integrated into SCM solutions to improve everything from process automation to overall decision-making. This includes greater data visibility (static and real-time data) as well as related management information system effectiveness.

In addition to fully automated decision-making, AI systems are also leveraging various forms of cognitive computing to optimize the combined efforts of artificial and human intelligence. For example, AI in SCM is enabling improved supply chain automation through the use of virtual assistants, which are used both internally (within a given enterprise) as well as between supply chain members (e.g. customer-supplier chains). It is anticipated that virtual assistants in SCM will leverage an industry-specific knowledge database as well as company, department, and production-specific learning.

AI-enabled improvements in supply chain member satisfaction causes a positive feedback loop, leading to better overall SCM performance. One of the primary goals is to leverage AI to make supply chain improvements from production to consumption within product-related industries as well as create opportunities for supporting "servitization" of products in a cloud-based "as a service" model. AI will identify opportunities for supply chain members to have greater ownership of "outcomes as a service" and control of overall product/service experience and profitability.

With Internet of Things (IoT) technologies and solutions taking an ever-increasing role in SCM, the inclusion of AI algorithms and software-driven processes with IoT represents a very important opportunity to leverage the Artificial Intelligence of Things (AIoT) in supply chains. More specifically, AIoT solutions leverage the connectivity and communications power of IoT, along with the machine learning and decision-making capabilities of AI, as a means of optimizing SCM by way of data-driven managed services.

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction2.1 Supply Chain Management2.1.1 Challenges2.1.2 Opportunities2.2 AI in SCM2.2.1 Key AI Technologies for SCM2.2.2 AI and Technology Integration

3.0 AI in SCM Challenges and Opportunities3.1 Market Dynamics3.1.1 Companies with Complex Supply Chains3.1.2 Logistics Management Companies3.1.3 SCM Software Solution Companies3.2 Technology and Solution Opportunities3.2.1 Leverage Artificial Intelligence (AI)3.2.1.1 Integrate AI with Existing Processes3.2.1.2 Integrate AI with Existing Systems3.2.2 Integrate AI with Internet of Things (IoT)3.2.2.1 Leverage AIoT Platforms, Software, and Services3.2.2.2 Leverage Data as a Service Providers3.3 Implementation Challenges3.3.1 Management Friction3.3.2 Legacy Processes and Procedures3.3.3 Outsource AI SCM Solution vs. Legacy Integration

4.0 Supply Chain Ecosystem Company Analysis4.1 Vendor Market Share4.2 Top Vendor Recent Developments4.3 3M4.4 Adidas4.5 Amazon4.6 Arvato SCM Solutions4.7 BASF4.8 Basware4.9 BMW4.10 C. H.Robinson4.11 Cainiao Network (Alibaba)4.12 Cisco Systems4.13 ClearMetal4.14 Coca-Cola Co.4.15 Colgate-Palmolive4.16 Coupa Software4.17 Descartes Systems Group4.18 Diageo4.19 E2open4.20 Epicor Software Corporation4.21 FedEx4.22 Fraight AI4.23 H&M4.24 HighJump4.25 Home Depot4.26 HP Inc.4.27 IBM4.28 Inditex4.29 Infor Global Solutions4.30 Intel4.31 JDA4.32 Johnson & Johnson4.33 Kimberly-Clark4.34 L'Oreal4.35 LLamasoft Inc.4.36 Logility4.37 Manhattan Associates4.38 Micron Technology4.39 Microsoft4.40 Nestle4.41 Nike4.42 Novo Nordisk4.43 NVidia4.44 Oracle4.45 PepsiCo4.46 Presenso4.47 Relex Solution4.48 Sage4.49 Samsung Electronics4.50 SAP4.51 Schneider Electric4.52 SCM Solutions Corp.4.53 Splice Machine4.54 Starbucks4.55 Teknowlogi4.56 Unilever4.57 Walmart4.58 Xilinx

5.0 AI in SCM Market Case Studies5.1 IBM Case Study with the Master Lock Company5.2 BASF: Supporting smarter supply chain operations with cognitive cloud technology5.3 Amazon Customer Retention Case Study5.4 BMW Employs AI for Logistics Processes5.5 Intelligent Revenue and Supply Chain Management5.6 AI-Powered Customer Experience5.7 Rolls Royce uses AI to safely transport its Cargo5.8 Robots deliver medicine, groceries and packages with AI5.9 Lineage Logistics Company Case Study

6.0 AI in SCM Market Analysis and Forecasts 2021 - 20266.1 AI in SCM Market 2021 - 20266.2 AI in SCM by Solution 2021 - 20266.2.1 Platforms6.2.2 Software6.2.3 AI as a Service6.3 AI in SCM by Solution Components 2021 - 20266.3.1 Hardware6.3.1.1 Non-IoT Device6.3.1.2 IoT Embedded Device6.3.1.2.1 Security Devices6.3.1.2.2 Surveillance Robots and Drone6.3.1.2.3 Networking Devices6.3.1.2.4 Smart Appliances6.3.1.2.5 Healthcare Device6.3.1.2.6 Smart Grid Devices6.3.1.2.7 In-Vehicle Devices6.3.1.2.8 Energy Management Device6.3.1.3 Components6.3.1.3.1 Wearable and Embedded Components6.3.1.3.1.1 Real-Time Location System (RTLS)6.3.1.3.1.2 Barcode6.3.1.3.1.3 Barcode Scanner6.3.1.3.1.4 Barcode Stickers6.3.1.3.1.5 RFID6.3.1.3.1.6 RFID Tags6.3.1.3.1.7 Sensor6.3.1.3.2 Processors6.3.2 Software6.3.3 Services6.3.3.1 Professional Services6.4 AI in SCM by Management Function 2021 - 20266.4.1 Automation6.4.2 Planning and Logistics6.4.3 Inventory Management6.4.4 Fleet Management6.4.5 Virtual Assistance6.4.6 Freight Brokerage6.4.7 Risk Management and Dispute Resolution6.5 AI in SCM by Technology 2021 - 20266.5.1 Cognitive Computing6.5.2 Computer Vision6.5.3 Context-aware Computing6.5.4 Natural Language Processing6.5.5 Predictive Analytics6.5.6 Machine Learning6.5.6.1 Reinforcement Learning6.5.6.2 Supervised Learning6.5.6.3 Unsupervised Learning6.5.6.4 Deep Learning6.6 AI in SCM by Industry Vertical 2021 - 20266.6.1 Aerospace and Government6.6.2 Automotive and Transportation6.6.3 Retail and Consumer Electronics6.6.4 Consumer Goods6.6.5 Healthcare6.6.6 Manufacturing6.6.7 Building and Construction6.6.8 Others6.7 AI in SCM by Deployment 2021 - 20266.7.1 Cloud Deployment6.8 AI in SCM by AI System 2021 - 20266.9 AI in SCM by AI Type 2021 - 20266.10 AI in SCM by Connectivity6.10.1 Non-Telecom Connectivity6.10.2 Telecom Connectivity6.10.3 Connectivity Standard6.10.4 Enterprise6.11 AI in SCM Market by IoT Edge Network 2021 - 20266.12 AI in SCM Analytics Market 2021 - 20266.13 AI in SCM Market by Intent Based Networking 2021 - 20266.14 AI in SCM Market by Virtualization 2021 - 20266.15 AI in SCM Market by 5G Network 2021 - 20266.16 AI in SCM Market by Blockchain Network 2021 - 20266.17 AI in SCM by Region 2021 - 20266.17.1 North America6.17.2 Asia Pacific6.17.3 Europe6.17.4 Middle East and Africa6.17.5 Latin America6.18 AI in SCM by Country6.18.1 Top Ten Country Market Share6.18.2 USA6.18.3 China6.18.4 Canada6.18.5 Mexico6.18.6 Japan6.18.7 UK6.18.8 Germany6.18.9 South Korea6.18.10 France6.18.11 Russia

7.0 Summary and Recommendations

For more information about this report visit https://www.researchandmarkets.com/r/bxs2vn

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Worldwide Artificial Intelligence in Supply Chain Management Industry to 2026 - Featuring 3M, Adidas and Amazon - PRNewswire

Artificial intelligence has transformed the business environment drastically. What began as a rule-based automation system is now capable of simulating human interaction. Artificial intelligence is not only exceptional because of the human capabilities. As compared to human equivalents, an advanced AI algorithm provides better speed and capacity at a much lower price.

Today, we are already related to AI in some way or the other, whether it is Siri,or Alexa, thanks to technological innovations. Yeah, the technology is still in its early stages, but more businesses are engaging in machine learning, suggesting that AI products and applications can expand rapidly in the immediate future.

AI inContent and news organizations

AI systems are increasingly being used by content and news organisations to discover data from various sources and instantly summarizeit into content or supporting analysis for those articles. Machine learning algorithms have been shown to be capable of detecting variations in textual data and extracting valuable knowledge that appropriately summarizes the information contained inside. Journalistic organizations can easily keep up with current events and produce content that accurately summarizes evolving circumstances by applying these sophisticated algorithms to vast amounts of data from press releases, tweets, articles, and other unstructured content.

Super Intelligence

BBN Times mentioned thatartificial intelligence is not only good at problem solving but it is also demonstrating empathy. AI has developed spontaneous emotions of its own accord. The company Cogito, founded by Joshua Fest and Dr Sandy Pentland, melds together machine learning with behavioral adaptation, supported by the latest breakthroughs inbehavioralscience.

The result is jarring to those who are used to AI being a benign force ready to work off dry data, but incredibly beneficial in thehigh-volumecustomer service arena and highly promising when we look to thefuture of artificial intelligence, and how it can continue to improve human life.

AI in Healthcare

The role of AI-powered technologies in next-generation healthcare technology is being recognized by the health sector. AI is thought to have the ability to enhance every phase of healthcare operations and service. For example, the economic benefits that AI can bring to the healthcare sector are a crucial motivator for AI implementation. AI systems are expected to save the US $150 billion in healthcare costs by 2026. The shift from a reactive to a proactive healthcare paradigm, concentrating on health treatment rather than curing diseases, is responsible for a significant portion of these cost savings. As a result, fewer hospitalizations, doctor appointments, and procedures are expected. AI-based innovation will play a key role in assisting people in maintaining their wellbeing by continuous tracking and coaching, as well as ensuring earlier diagnosis, personalized care, and more effective reassessments.

AI in Entertainment

Today theentertainment industry is allset to undergo a different kind oftransformation. AI would make the future of the industry more social, personalized, and entertaining. Virtual reality,allyrobots can gradually penetrate the home as the use of sensors and hardware expands. Additionally, consumers will be able to converse with entertainment devices.

Media companies will be able to personalize entertainment to previously unthinkable levels thanks to this technology. Youll possibly be able to build your own entertainment channel using AI in the not-too-distant future.

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The Spectacular Growth of Artificial Intelligence Today - Analytics Insight

In an attempt to make this possible, the Central Board of Secondary Education (CBSE) has introduced artificial intelligence as an individual subject for the 9th grade in the academic year of 2019-2020 and for the 11th grade in the academic year of 2020-2021 in all CBSE affiliated schools.

Artificial intelligence is already a part of the education system in the form of tools that help develop skills and testing systems. This technology can help drive efficiency, customization, and streamline administrative tasks to give teachers the time and freedom for better adaptability. By combining the best attributes of machines and teachers, the aim of artificial intelligence is to make everything work together seamlessly for the best outcomes that will benefit the students.

All AICTE (All India Council For Technical Education) approves institutions have been suggesting to offer artificial intelligence as an elective subject in B.Tech courses and also start individual B. Tech courses focusing on artificial intelligence and data science to augment the field of artificial intelligence and data analysis. So far, only the Indian Institutes Of Technology (IITs) can have their own curriculum, academic, and research collaborations with institutions and universities across the world, owing to their acts and statutes.

Most of these IITs offer many artificial intelligence-related courses like deep learning foundations and applications, the foundation of artificial intelligence and machine learning, reinforcement learning, probabilistic reasoning in artificial intelligence, predictive and prescriptive data analytics, deep learning, system identification, cyber-physical security, digital image processing, etc. Apart from these courses, IITs also conduct short-term programs on artificial intelligence for working professionals and other interested candidates.

All of the above information provided was given by the Union Minister For Education, India, Ramesh Pokhriyal in a written statement in the Lok Sabha.

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Artificial Intelligence Will Become A Part Of The Indian School Curriculum - Analytics Insight

Guruprasad Gaonkar

In 2020 our personal and professional relationships and perceptions have undergone a sea change and this includes our relationship with our money as well. According to a survey that Oracle did with personal finance expert Farnoosh Torabi, 83% of Indians (including business leaders) trust robots more than humans when it comes to managing their finances.

Some of the key India data that suggests this consequential shift reveals that 85% of Indian consumers believe that robots can help them with managing their finances. Responding to this change in consumer mindset, Indian business leaders, that is, 93% have shared that they have invested in digital payment capabilities and 81% have created new forms of customer engagement or changed their business models by embracing newer technologies. I am not surprised with the study as AI and ML are seeing unprecedented adoption, with the pandemic playing catalyst, says Kannan Sugantharaman, CFO, Omega Healthcare.

Around 90% of business leaders believe robots will replace finance professionals, and more than a third (67%) of them believe that itll happen by 2025. Guruprasad Gaonkar, Global SaaS Go-to-Market Leader, Cloud Business Group, Oracle, observes that many forward looking companies have already started the process by adopting AI powered ERP, with more radical transformation coming from the possibility of bringing it together with Blockchain. McDonalds and Wipro are some of companies that have already moved on from previously people dependent approach to eliminate manual guesswork specifically with enterprise performance management. Echoing the sentiment, Dinesh Modi, CFO, Cactus Communications, says that ERP cloud has given us the opportunity to work with technologies like robotic process automation (RPA) and streamline the process whereby the same team can deliver higher output.

Businesses will need to re-align themselves with the power of the trinity AI, IoT and Blockchain. Almost every activity that goes within the finance function across sectors can be planned and agreed upon within ERP cloud applications and then encrypted into an immutable ledger capable of executing different transactions autonomously and at a defined moment in time.

Its time to rethink the money management. Businesses need to provide new business models and payment methods that remove friction for customers. Sugantharaman foresees finance as a function undergoing transformation. Elements like Cost, Control and Compliance can be more efficiently managed by AI based tools today leaving business leaders and CFOs to tend to more strategic roles facilitating growth, investments, enablement and value creation through digital technologies.

In a nutshell, AI will transform the role of the CFO, introducing the touchless finance factory and the creation of a next generation workplace. As Gaonkar puts it, being technology enabled is a pass, being technology led is in vogue.

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Artificial Intelligence & Finance: Two sides of the same coin in new normal - The Financial Express

Since 2019 the FDAs crosscutting work has implemented artificial intelligence (AI) as part of the its New Era of Smarter Food Safety initiative. This new application of available data sources can strengthen the agencys public health mission with the goal using AI to improve capabilities to quickly and efficiently identify products that may pose a threat to public health by impeding their entry into the U.S. market.

On February 8 the FDA reported the initiation of their succeeding phase for AI activity with the Imported Seafood Pilot program. Running from February 1 through July 31, 2021, the pilot will allow FDA to study and evaluate the utility of AI in support of import targeting, ultimately assisting with the implementation of an AI model to target high-risk seafood productsa critical strategy, as the United States imports nearly 94% of its seafood, according to the FDA.

Where in the past, reliance on human intervention and/or trend analysis drove scrutiny of seafood shipments such as field exams, label exams or laboratory analysis of samples, with the use of AI technologies, FDA surveillance and regulatory efforts might be improved. The use of Artificial intelligence will allow for processing large amount of data at a faster rate and accuracy giving the capability for revamping FDA regulatory compliance and facilitate importers knowledge of compliance carrying through correct activity. FDA compliance officers would also get actionable insights faster, ensuring that operations can keep up with emerging compliance requirements.

Predictive Risk-based Evaluation for Dynamic Imports Compliance (PREDICT) is the current electronic tracking system that FDA uses to evaluate risk using a database screening system. It combs through every distribution line of imported food and ranks risk based on human inputs of historical data classifying foods as higher or lower risk. Higher-risk foods get more scrutiny at ports of entry. It is worth noting that AI is not intended to replace those noticeable PREDICT trends, but rather augment them. AI will be part of a wider toolset for regulators who want to figure out how and why certain trends happen so that they can make informed decisions.

AIs focus in this regard is to strengthen food safety through the use of machine learning and identification of complex patterns in large data sets to order to detect and predict risk. AI combined with PREDICT has the potential to be the tool that expedites the clearance of lower risk seafood shipments, and identifies those that are higher risk.

The unleashing of data through this sophisticated mechanism can expedite sample collection, review and analysis with a focus on prevention and action-oriented information.

American consumers want safe food, whether it is domestically produced or imported from abroad. FDA needs to transform its computing and technology infrastructure to close the gap between rapid advances in product and process technology solutions to ensure that advances translate into meaningful results for these consumers.

There is a lot we humans can learn from data generated by machine learning and because of that learning curve, FDA is not expecting to see a reduction of FDA import enforcement action during the pilot program. Inputs will need to be adjusted, as well as performance and targets for violative seafood shipments, and the building of smart machines capable of performing tasks that typically require human interaction, optimizing workplans, planning and logistics will be prioritized.

In the future, AI will assist FDA in making regulatory decisions about which facilities must be inspected, what foods are most likely to make people sick, and other risk prioritization factors. As times and technologies change, FDA is changing with them, but its objective remains in protecting public health. There is much promise in AI, but developing a food safety algorithm takes time. FDAs pilot program focusing on AIs capabilities to strengthen the safety of U.S. seafood imports is a strong next step in predictive analytics in support of FDAs New Era of Smarter Food Safety.

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Regulatory Cross Cutting with Artificial Intelligence and Imported Seafood | FoodSafetyTech - FoodSafetyTech

Whether its police brutality, the disproportionate over-exposure of racial minorities to COVID-19 or persistent discrimination in the labour market, Europe is waking up to structural racism. Amid the hardships of the pandemic and the environmental crisis, new technological threats are arising. One challenge will be to contest the ways in which emerging technologies, like Artificial Intelligence (AI), reinforce existing forms of discrimination.

From predictive policing systems that disproportionately score racialised communities with a higher risk of future criminality, all the way to the deployment of facial recognition technologies that consistently mis-identify people of colour, we see how so called neutral technologies are secretly harming marginalised communities.

The use of data-driven systems to surveil and provide a logic to discrimination is not novel. The use of biometric data collection systems such as fingerprinting have their origins in colonial systems of control. The use of biometric markers to experiment, discriminate and exterminate was also a feature of the Nazi regime.

To this day in the EU, we have seen a number of similar, worrying practices, including the use of pseudo-scientific lie detection technology piloted on migrants in the course of their visa application process. This is just one example where governments, institutions and companies are extracting data from people in extremely precarious situations.

Human rights mustnt come second in the race to innovate; they should rather define innovations that better humanity

Many of the most harmful AI applications rely on large datasets of biometric data as a basis for identification, decision making and predictions. What is new in Europe, however, is that such undemocratic projects could be legitimised by a policy agenda promoting the uptake of AI in all areas of public life.

The EU policy debate on AI, while recognising some risks associated with the technology, has overwhelmingly focused on the purported widespread benefits of AI. If this means shying away from clear legal limits in the name of promoting innovation, Europes people of colour will be the first to pay the price.

Soon, MEPs will need to take a position on the European Commissions legislative proposal on AI. While EU leaders such as Executive Vice-President Vestager and Vice-President Jourov have spoken of the need to ensure AI systems do not amplify racism, the Commission has been under pressure from tech companies like Google to avoid over-regulation. Yet, the true test of whether innovations are worthwhile is how far they make peoples lives better.

When industry claims human rights safeguards will hinder innovation, they are creating a false distinction between technological and social progress. Considerations of profit should not be used to justify discriminatory or other harmful technologies.

Human rights mustnt come second in the race to innovate; they should rather define innovations that better humanity. A key test will be how far the EUs proposal recognises this. As the Commission looks to balance the aims of promoting innovation and ensuring technology is trustworthy and human-centric, it may suggest a number of limited regulatory techniques.

The first is to impose protections and safeguards only for the most high-risk of AI applications. This would mean that, despite the unpredictable and ever-changing nature of machine learning systems, only a minority of systems would actually be subject to regulation, despite the harms being far more widespread.

The second technique would be to take limited actions requiring technical de-biasing, such as making datasets more representative. However, such approaches rarely prevent discriminatory outcomes from AI systems. Until we address the underlying causes of why data encodes systemic racism, these solutions will not work.

Both of these proposals would provide insufficient protection from systems that are already having a vastly negative impact on human rights, in particular to those of us already over-surveilled and discriminated against. What these solutions fail to address is that, in a world of deeply embedded discrimination, certain technologies will, by definition, reproduce broader patterns of racism.

Some decisions are too important and too dangerous to be made by an algorithm. This is the EUs opportunity to make people a priority and stop discriminatory AI before its too late

There is no quick fix, no risk assessment sophisticated enough, to undo centuries of systemic racism and discrimination. The problem is not just baked into the technology, but into the systems in which we live. In most cases, data-driven systems will only make discrimination harder to pin down and contest. Digital, human rights and antiracist organisations have been clear that more structural solutions are needed.

One major step put forward by the pan-European Reclaim Your Face campaign is an outright ban on destructive biometric mass surveillance technologies. The campaign, coordinated by European Digital Rights (EDRi), includes 45 organisations calling for a permanent end to technologies such as facial, gait, emotion, and ear canal recognition that target and disproportionally oppress racialised communities.

The Reclaim Your Face European Citizens Initiative petition aims to collect one million signatures to call for a Europe-wide ban and promote a future without surveillance, discrimination and criminalisation based on how we look or where we are from.

Beyond facial recognition, EDRi, along with 61 other human rights organisations, have called on the European Union to include red-lines or legal limits on the most harmful technologies - in its laws on AI, especially those that deepen structural discrimination. The upcoming AI regulation is the perfect opportunity to do this.

AI may bring significant benefits to our societies, but these benefits must be for us all. We cannot accept technologies that only benefit those who sell and deploy them. This is especially valid in areas rife with discrimination. Some decisions are too important and too dangerous to be made by an algorithm. This is the EUs opportunity to make people a priority and stop discriminatory AI before its too late.

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Artificial Intelligence: Reinforcing discrimination - The Parliament Magazine

How can culinary traditions be preserved, Spratt asked, when food is ultimately meant to be consumed? UNESCO recognizes French cuisine as an intangible heritage, which it defines as not the cultural manifestation itself, but rather the wealth of knowledge and skills that is transmitted through it from one generation to the next.

The gastronomic algorithms project, in contrast, emphasizes the cultural manifestation itself. Specifically, the project focuses on the artistic dimension of plating through Passards use of collages to visually conceive of actual plates of food. Taking this one step further, the project also explores how fruit-and-vegetable-embellished paintings by the Italian Renaissance artist Giuseppe Arcimboldo (1526-1593) could be reproduced through the use of artificial intelligence tools.

Spratt then asked the leading question of her research: How could GANs, a generative form of AI, emulate the culinary images, and would doing so visually reveal anything about the creative process between the chefs abstracted notions of the plates and collages, and their actual visual execution as dishes?

Experimenting With Datasets

Although Passards collages are a source of inspiration for his platings, a one-to-one visual correlation between the appearance of both does not exist. The dataset initially comprised photos posted by Passard on Instagram, images provided by the restaurants employees, and photos captured by Spratt at L'Arpge during each of the different seasons. This was later supplemented by images of vegetables and fruits on plates, as well as sliced variations procured from the internet using web scraping tools.

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Artificial Intelligence and the Art of Culinary Presentation - Columbia University

Meta Description: Artificial Intelligence is increasing in sophistication year on year. It will help to define the future of how humans live. Here we explore this future.

The onward progression of technology is unstoppable. There are so many applications of Artificial Intelligence, in online gaming to building management and into the workplace. While we may be concerned by the apocalyptic application of AI shown in the movies, the experts suggest that the rise of artificial intelligence will make most of us more money over the next ten years. Is money everything when we may lose our career and, more vitally, our free will?

Much of the AI is code-driven. Algorithms are used to mimic the intelligence of humans and offer previously unimagined opportunities and potential threats. Experts suggest that this networked AI will make us all more effective but it will also threaten our levels of autonomy. There is a real possibility that computers will match and maybe even surpass that of humans. The smart systems we use in our everyday lives are meant to save us time and money and improve our lives, helping to customize our experience into the future.

The positives

Most optimism about artificial intelligence was research for health care. There are many applications of this technology in the diagnosis and treatment of patients. It might even help older people live fuller and healthier lives. While we should be concerned that this technology driven world would require a massive amount of our data to make it work, the benefits might outweigh the threats.

Education is another area where the changes might be revolutionary. It could transform the way we learn, moving us away from formal models to informal education systems. AI should be able to predict what you need to develop next and remove the need to know or memorize details.

While there is a lot of optimism and excitement about the technology there were also many notes of worry and concern. Some of these concerns include:

Maintaining control of our livesWe maintain our agency because we can make our own decisions. While we are flawed, it is this possibility that we make errors that makes us humans. Some failures, the non-optimal option that people have the capacity to take, might actually turn out to be a happy accident. Therefore, with AI will be the loss of this right to make a mistake and instead we will be interdependent on the tech and the power systems that control them.

Open to abuseMost companies seeking to use AI want to make a profit or are organizations that hope to gain power. Therefore, the use of data can be to surveil the population and make choices to manipulate based on what has been found out. While we would hope for the best qualities in our business and political leaders, it is not often that ethics are built into digital systems. As the world is fully networked, it is also not easy to regulate.

Loss of our jobsSo, while most people predict that AI will make a lot of people more affluent, for a lot of people it will mean the loss of jobs. The advantage of machines is that they can complete repetitive jobs efficiently and accurately every time. Machines can perform in situations that are too dangerous for humans.

The real consequence is that the gap between the haves and the have nots will widen and there will be increasing social unrest at inequalities.

We are dependentWhile we believe that this technology is augmenting human capabilities, we are more likely to allow skills and understanding to lapse, devolving this to the machine. An optimistic view of this is that we can then turn our attention to deeper learning. However, the likelihood is that we become more and more dependent on the machine and will not be able to function without them. Also, the chance to usurp our lives with the interruption of power supplies could prove a significant threat to societies.

Our power supplies and reliance on networks opens us to cybercrime and the weaponization of information. If you want to increase your levels of anxiety a little more, consider the number of autonomous weapons systems around the world that are controlled by AI. If you are starting to think Terminator here, we are a long way from these computers having a consciousness and acting independent of humans.

In shortThe possibilities for AI and our human future are endless. There is much potential for using it for a common good. If we can just develop an aspiration and ambition to uphold values, then AI could enhance our future.

However, we have to be realistic. Such technology offers opportunity for abuse and we must move forward with caution, using all our human intelligence to put safeguards in place that will protect ourselves.

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Artificial Intelligence and the Future of Humans - LA Canyon News

As the new administration staffs up and Capitol Hill lawmakers begin to contemplate post-pandemic priorities, countering Chinas advances in artificial intelligence and other disruptive technologies has emerged as a major driving force for US policymakers. This alert provides a summary of expected new AI-related legislation, an overview of a recent report by the National Security Commission on Artificial Intelligence, highlights of the Biden Administrations approach to technology/AI as well as the key AI-related policymakers in the Administration and in Congress.

Three developments in the last month signal a focused mindset of policymakers in Washington, DC to counter China on technology:

Washington sees maintaining and extending US leadership in technological innovation as a vital national security imperative, both:

While a strategic imperative to move fast and out-compete China is prevalent in the highest levels of the federal government, progressive elements of the Democratic majorities in the Congress may advocate for cautionary breaks and regulatory guardrails to this rapid technology development, such as AI algorithmic impact assessments, audits and penalties for developers of AI applications.Europeis currently considering some of the strictest AI regulations in the world today, and US policymakers will likely face pressure across the Atlantic to issue further guidance or even consider targeted, agency-specific regulations of high-risk AI applications.

AI and the great power competition

The March 1 NSCAI final report could be seen by some as a wake-up call since the report highlights that other nations are not standing idly by and thus some experts believethe Defense Department must move beyond the legacy systems that have defined military planning for decades. The findings, quarterly recommendations and stark conclusions of the report have reverberated in high-level defense and foreign policy circles and sounded the alarm to members of congress, staff and the general public.

Eric Schmidt, Chairman of the NSCAI, declared the AI competition with China is a national emergency and a threat to our nation unless we get our act together with respect to focusing on AI in the federal government and international security.

The 15-member Commission composed of technologists, business executives, academic leaders and national security professionals was created under the fiscal year 2019 National Defense Authorization Act (NDAA) to consider the methods and means necessary to advance the development of artificial intelligence, machine learning, and associated technologies to comprehensively address the national security and defense needs of the United States.

Among the NSCAI reports takeaway headlines:

The Commissioners focused on four pillars for immediate action:

Many of these recommendations, which span the entire federal government, have a good shot at serious legislative consideration, with the fiscal year 2022 National Defense Authorization Act being the most likely vehicle to carry many of the policy proposals.

New administration, similar competitive tech concerns about China

While President Biden has used his executive powers to reverse a host of policies enacted by his predecessor, one area of potential continuity from the Trump era is an aggressive posture towards China.

Other Biden Administration technology/AI initiatives and personnel

The pending rule is part of a broader effort to secure US supply chains, bolster US manufacturing and enhance the role of science, particularly at a time when a global shortage of semiconductor chips is causing severe production cutbacks in automotive and consumer electronics manufacturing.

President Biden hasannounceda number of appointments and nominations of officials who will take leading roles on AI and related issues and has raised the profile of key posts with jurisdiction over cyber and technology issues.

In his first major speech as Americas top diplomat, Secretary of State Anthony Blinken said:

Advancing US tech to counter China a big priority on Capitol Hill

Senator Schumer, leader of the newly minted Democratic majority in the Senate, has directed the chairs and members of our relevant committees to start drafting a legislative package to out-compete China and create new American jobs.

Congress laid some of the groundwork for implementing a more comprehensive national AI strategy with the passage on New Years Day (over Trumps veto) of the FY 2021 NDAA, which incorporated theNational AI Initiative Act.The White House on January 12 fulfilled the laws requirement to establish the National AI Initiative Office, responsible for coordinating AI research and policymaking across government, industry and academia.

The National AI Initiative Act, also known as Division E of the NDAA, was the most significant AI legislation to date to be enacted by Congress and will serve as thefoundationfor non-defense AI policy for the federal government in the years ahead. Division E established a coordinated, civilian-led federal initiative to accelerate research and development and encourage investments in trustworthy AI systems for the economic and national security of the United States. The legislation authorizes policies and significant funding for the National Science Foundation (NSF), National Institute of Standards and Technology (NIST) and Department of Energy.

In the 117th congress, a shift of focus will turn to monitoring implementation of this legislation and appropriating additional dollars to resource the initiative. Democratic majorities in both the House and Senate can be expected to apply a greater amount of attention and scrutiny over AI applications and their outcomes. Industry should expect increased policy and regulatory focus on ensuring accountability of AI through impact assessments and audits of AI algorithms. In her confirmation hearing, newly sworn in Commerce Secretary Gina Raimondo pledged to work with Congress on a bipartisan basis as part of the Advisory Committee on AI required by the defense policy bill. Raimondos department has jurisdiction over key science policy bureaus, including NIST.

The House Armed Services Committee has established a new Subcommittee on Cyber, Innovative Technologies, and Information Systems, with Representative James Langevin (D-RI) as chair and House AI Caucus member Elise Stefanik (R-NY) as ranking member. AI Caucus member and Endless Frontiers Act sponsor Representative Ro Khanna (D-CA) is also on this subcommittee.

Additional key congressional players on AI issues

Senator Rob Portman (R-OH), co-founder and co-chair of the Senate AI Caucus, announced that his current term will be his last and he will not seek re-election in 2022. But he has demonstrated that he will continue to be a leading voice on AI issues over the next two years, including in his capacity as ranking member of the Homeland Security and Governmental Affairs Committee which, among other responsibilities, has authority to investigate the efficiency, economy and effectiveness of all agencies and departments of the government.

Senator Martin Heinrich(D-NM), fellow co-chair and co-founder of the AI Caucus, is moving to the Appropriations Committee. He authored the SenatesArtificial Intelligence Initiative Actin 2019.

Many of the provisions included in that legislation became law via the FY21 NDAA being enacted on New Years Day 2021. Senator Heinrich is likely to continue pushing forresponsible and trustworthyAI funding and policies for government agencies while providing congressional oversight of the newly created White House National AI Initiative Office.

Representative Jerry McNerney (D-CA)continues as the Democratic Co-Chair of the House AI Caucus. He is particularly passionate and focused on AI workforce and research issues and is a member of the House Science Committee.

Representative Anthony Gonzalez (R-OH) will take over as the Republican co-chair of the House AI Caucus. Gonzalez, now in his second term, was not a member of the AI Caucus previously, but he was part of abipartisan group of House memberswho called on NIST to develop a framework on strategies, guidelines and best practices for AI that will bolster innovation and ethical practices in developing and implementing artificial intelligence across the US. He is also interested in AI impacts on the workforce as a representative from the rustbelt.

Current AI Caucus membership in the 117thCongress:

Senate AI Caucus

CO-CHAIRS

Martin Heinrich (D-NM)

Rob Portman (R-OH)

MEMBERS

Brian Schatz (D-HI)

Joni Ernst (R-IA)

Gary Peters (D-MI)

Mike Rounds (R-SD)

Maggie Hassan (D-NH)

House AI Caucus

CO-CHAIRS

Jerry McNerney (D-CA-09)

Anthony Gonzalez (R-OH-16)

MEMBERS

Don Beyer (D-VA-08)

GK Butterfield (D-NC-01)

Andr Carson (D-IN-07)

Emanuel Cleaver II (D-MO-05)

Suzan DelBene (D-WA-01)

Mark DeSaulnier (D-MA-11)

Nanette Diaz Barragn (D-CA-44)

Debbie Dingell (D-MI-12)

Anna G. Eshoo (D-CA-18)

Bill Foster (D-IL-11)

Josh Gottheimer (D-NJ-05)

Pramila Jayapal (D-WA-07)

Henry C. "Hank" Johnson (D-GA-04)

Ro Khanna (D-CA-17)

Derek Kilmer (D-WA-06)

Brenda Lawrence (D-MI-14)

Ted Lieu (D-CA-33)

Michael McCaul (R-TX-10)

Bobby Rush (D-IL-01)

Brad Sherman (D-CA-30)

Darren Soto (D-FL-09)

Elise Stefanik (R-NY-21)

Steve Stivers (R-OH-15)

Marc Veasey (D-TX-33)

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Technology, artificial intelligence in focus for the Biden Administration and the 117th Congress Seen through the lens of competition with China -...

The Indo-U.S. Science and Technology Forums (IUSSTF) US India Artificial Intelligence (USIAI) Initiative was launched on Wednesday (17 March).

IUSSTF is a bilateral organization funded by the department of Science and Technology (DST), Government of India and the US Department of States.

USIAI Initiative focuses on Artificial Intelligence (AI) cooperation in critical areas prioritized by both countries. It will serve as a platform to discuss opportunities, challenges, and barriers for bilateral AI research and development collaboration, enable AI innovation, help share ideas for developing an AI workforce, and recommend modes and mechanisms for catalyzing partnerships, DST said in a statement.

Indo-US relationship in the field of science and technology is very old and collaborations have resulted in great benefits for both the countries. We need to further scale it up in various fields, and AI can play a major role in the future. We have identified the barriers for growth in India that could be useful for the United States too, said Professor Ashutosh Sharma, Secretary, DST.

The US-India AI Initiative will provide an opportunity for key stakeholder groups to share experiences, identify new research and development areas that would benefit from synergistic activities, discuss the emerging AI landscape, and address the challenges of developing an AI workforce.

The ambitious flagship initiative, USIAI, leverages IUSSTFs unique ability to bring together key stakeholders from India and the United States to create synergies that address challenges and opportunities at the interface of science, technology, and society.

Over the next year, IUSSTF will conduct a series of roundtables and workshops to gather input from different stakeholder communities and prepare white papers that identify technical, research, infrastructure, and workforce opportunities and challenges, and domain-specific opportunities for research and development in healthcare, smart cities, materials, agriculture, energy, and manufacturing.

More:

US India Artificial Intelligence Initiative Launched, To Boost Bilateral Cooperation In Research And Development - Swarajya