Precision medicine, a technology still in its infancy, is an approach to treatment that uses information about an individual's medical history and genetic profile and relates it to the information of many others to find patterns that can help prevent, diagnose or treat a disease.  "Precision medicine is one of the most trending subjects in basic and medical science today," sais Zeeshan Ahmed, an assistant professor of medicine at Rutgers Robert Wood Johnson Medical School. "Major reasons include its potential to provide predictive diagnostics and personalized treatment to variable known and rare disorders. However, until now, there has been very little effort exerted in organizing and understanding the many computing approaches to this field."

In the past five years, interest in applying artificial intelligence (AI) approaches in drug research and development (R&D) has surged. Driven by the expectation of accelerated timelines, reduced costs and the potential to reveal hidden insights from vast datasets, more than 150 companies with a focus on AI have raised funding in this period. And the number of financings and average amount raised soared in 2021. At the forefront of this field are companies harnessing AI approaches such as machine learning (ML) in small-molecule drug discovery, which account for the majority of financings backed by venture capital (VC) in recent years, as well as some initial public offerings (IPOs) for pioneers in the area.

The spectrum of approaches for the application of AI in small-molecule drug discovery can be illustrated by a selection of companies that have raised substantial funding (Table 1) and/or signed major deals with large pharma companies (Table 2) in the past two years. Some of these companies are mainly focused on a particular stage of the drug discovery pipeline, such as target identification or compound screening, while others are aiming to establish end-to-end platforms in which AI tools are at the core in each step.

see more: https://www.nature.com/articles/d43747-022-00104-7

How Audi Is Designing the Production of the Future. From modular assembly as a response to increasing product variety, to virtual assembly planning for the resource-efficient design of infrastructure or the local server solution Edge Cloud 4 Production that is a paradigm shift in factory automation: Audi is building a fully networked, highly efficient, and sustainable way of production that uses new technologies and concepts to successfully meet the demands of the future. In doing so, Audi is looking at manufacturing as a whole - from the individual employee to the fully automated production cycle. read more: https://www.audi-mediacenter.com/en/presskits/smart-production-14757   Miso’s Flippy 2 and Sippy products ensure restaurant employees spend “less time at the fryer and drink stations and more time in front of customers,” Miso said in the press release. Several major restaurant chains are exploring automated robotics solutions to offset wage and inflation hikes as the labor shortage holds steady. Earlier this month, Panera said it will test Miso’s artificial intelligence-enabled coffee monitoring system, CookRight Coffee, at two locations. The technologies can also be labor-saving, as QSRs don’t need as many employees at the drinks and fry stations to ramp up output when these robots are deployed, Miso CEO Mike Bell said in an email. more insights: https://www.restaurantdive.com/news/jack-in-the-box-Miso-test-robots-to-combat-labor-shortage/622675/

Transporeon, the leading Transportation Management Platform, announced on August 22nd, 2022 the acquisition of Tracks, a Berlin-based start-up with the mission to decarbonise the transport industry. AI-based analytics and prediction tools that take carbon visibility to another level, facilitating the reduction in one’s carbon footprint through the targeted use of primary data. Tracks is a carbon visibility tool providing data solutions to monitor and manage carbon emissions across all transport modes. To do this, the company uses AI-based analytics and prediction tools to enable shippers, carriers and logistics service providers to collect and optimise emissions data at source.

see more: https://www.transporeon.com/en/company/press/transporeon-acquires-tracks

Argo AI, 412 Food Rescue, and Parkhurst Launch Autonomous Food Delivery. To help tackle food insecurity, leading autonomy products and services company Argo AI has partnered with 412 Food Rescue and Parkhurst Dining to launch an autonomous vehicle delivery service to transport surplus food to local nonprofits in Pittsburgh. The service will pair Argo autonomous vehicles with 412 Food Rescue partners to pick up and transport meals to nonprofits who offer food assistance and supplies in the region. With a team of more than 2,000 people across the U.S. and Europe, Argo designs its Argo Autonomy Platform and Solutions to support autonomous ridesharing and goods delivery to benefit communities around the world.

more about this: https://www.argo.ai/company-news/argo-ai-412-food-rescue-and-parkhurst-launch-autonomous-food-delivery/

When it comes to geospatial and mapping data and how they are leveraged by organizations, satellites continue to play a critical role when it comes to sourcing raw information. Getting that raw data into a state that can be usable by enterprises, however, is a different story. As a German company, LiveEO is one of a small but growing group of startups in Europe capitalizing on increasing interest in space among investors in recent years. LiveEO’s platform addresses a specific gap between space tech and enterprise data. Satellites are collectively producing more data about our world than ever before, covering not just physical objects in the most minute detail, but thermal progressions, how systems are moving and more.

read more: https://techcrunch.com/2022/08/04/armed-with-19-5m-liveeo-plots-a-big-data-course-between-satellite-geospatial-information-and-industry

 

Automated interpretation of industrial X-ray images. Digital detectors and highly automated inspections systems allow manufacturers to significantly optimize their quality control and assurance processes. Due to the higher throughput of parts, the evaluation and interpretation of X-ray images is starting to become a costly bottleneck. Advanced technologies like Automated Defect Recognition (ADR) and Artificial Intelligence (AI) have the potential to significantly reduce the required time per part. Depending on the inspection standard and requirements the algorithms can be implemented in an as an assistance to the operator or fully automated.. PFW Aerospace GmbH has implemented our Artificial Intelligence (AI) based ADR prototype in a production environment as an assistance tool to increase the throughput and process safety of X-ray image interpretation.

more about this: https://visiconsult.de/smart-inspection/

At Morgan Stanley, for example, Chief Data and Analytics Officer Jeff McMillan has focused for many years on a wealth management “next best action” system and communications platform. The system allows the firm’s Financial Advisors to identify customized investing opportunities at scale using machine learning, and the communications platform delivers them to clients on a regular basis. Artificial Intelligence (AI) has become crucial to highly demanding industries globally. The impact of AI in the accounting and finance industry is phenomenal, and it is also innovating how they operate and build products and services. Recent AI advancements are rapidly changing the face of accounting and finance in many ways. Labor and time-consuming tasks of finance and accounting, which include – audits, banking, tax preparation, bookkeeping, reporting, and payroll, have become successfully automated with the help of AI. With the implementation of emerging technologies to develop self-learning systems also getting integrated into accounting works, technological systems will carry on repetitive and time-intensive tasks, which will leave the analytical and managerial tasks to humans. From chatbots to actively handling the management accountant, from facing the regulations and requirements from clients to handling the time-consumed tasks, AI has a huge impact. According to Forbes, several reputed software vendors, such as Intuit, Sage, OneUp, and Xero, provide automated data entry and reconciliation options via Artificial Intelligence (AI) and Machine Learning (ML) technologies in organization bookkeeping. This has resulted in Chartered Professional Accountant professionals choosing a new kind of workforce so that they can well manage all the tasks without any hassles. see more: https://www.datasciencecentral.com/how-ai-will-impact-the-accounting-and-finance-industry

As millions of people transitioned to remote work during the pandemic, criminals took advantage of the increased volume of online activity. Scams proliferated, according to the FBI. Human traffickers and drug cartels, long seeking ways to circumvent regulators and law enforcement, refined their money laundering through online marketplaces and cryptocurrencies that afforded anonymity while connecting buyers and sellers, the U.S. Government Accountability Office reported. To adapt to these threats, regulators and law enforcement authorities began to turn to artificial intelligence and machine learning to battle bad actors. These tools help officials spot trends and set rules to help banks and other institutions identify and report suspicious transactions.

Meanwhile, the Securities and Exchange Commission proposed rules to crack down on financial cybercrimes. Even if government agencies and financial institutions could hire everyone they needed tomorrow, they would still need AI and machine learning to manage the deluge of cybercrime that is now routine. The massive scale of online activity and the scope of the cyberthreat today is too large for teams of people of any size to handle, even in the public sector. AI and machine learning can take on that work in three areas:

- AI helps officials in the discovery process, finding so-called “unknown unknowns,” or problems that remain hidden from regulators, as well as patterns in data across multiple firms and systems that point to emerging threats and new behavior patterns.

- Ninety-five percent of suspicious activity reports are false positives. Banks are inundating the U.S. Treasury’s Financial Crimes Enforcement Network with irrelevant SARs, wasting resources that regulators and financial institutions could put to better use in finding real crime. Using broader data sets to capture all known risks and reduce alerts, AI can cut down on false positives by more than 75 percent, discovering crime more effectively so resources can be refocused on other, more genuine threats.

- AI and machine learning can help law enforcement single out the worst bad actors and gather sufficient evidence against them. Identifying unknown relationships and linkages between entities and people, spotting unusual changes in behaviors across entities, digital tracking of activities, and other investigative technologies help law enforcement pinpoint the most mysterious and elusive bad actors perpetrating the most damaging crimes. Within mountains of data, AI can recognize the genuinely suspicious patterns and inconsistencies that are the telltale signs of drug and human trafficking organizations’ money laundering, for instance.

read more: https://www.c4isrnet.com/opinions/2022/08/18/federal-government-using-artificial-intelligence-to-fight-cybercrime/

UK Government Policy paper - Establishing a pro-innovation approach to regulating AI - Across the world, AI is unlocking enormous opportunities, and the UK is at the forefront of these developments.

read more: https://www.gov.uk/government/publications/establishing-a-pro-innovation-approach-to-regulating-ai/establishing-a-pro-innovation-approach-to-regulating-ai-policy-statement

 

In the National AI Strategy (UK), the government set out an ambitious ten-year plan for the UK to remain a global AI superpower. The UK is already a leader in many aspects of AI, with a thriving ecosystem and a strong track record of innovation. But there is more to do to harness the enormous economic and societal benefits of AI while also addressing the complex challenges it presents. Establishing clear, innovation-friendly and flexible approaches to regulating AI will be core to achieving our ambition to unleash growth and innovation while safeguarding our fundamental values and keeping people safe and secure. Our approach will drive business confidence, promote investment, boost public trust and ultimately drive productivity across the economy.

get the insights: https://www.gov.uk/government/publications/national-ai-strategy

 

Similiarly the EU is publishing numerous documents on the definition of AI and the constraints/differences of its use in public services.

see more: https://publications.jrc.ec.europa.eu/repository/handle/JRC129301