Mediaboss Marketing

The European Commission recently published a proposal for a regulation on artificial intelligence (AI). This is the first document of its kind to attempt to tame the multi-tentacled beast that is artificial intelligence.

The sun is starting to set on the Wild West days of artificial intelligence, writes Jeremy Kahn. He may have a point.

When this regulation comes into effect, it will change the way that we conduct AI research and development. In the last few years of AI, there were few rules or regulations: if you could think it, you could build it. That is no longer the case, at least in the European Union.

There is, however, a notable exception in the regulation, which is that is does not apply to international organizations like the United Nations.

Naturally, the European Union does not have jurisdiction over the United Nations, which is governed by international law. The exclusion therefore does not come as a surprise, but does point to a gap in AI regulation. The United Nations therefore needs its own regulation for artificial intelligence, and urgently so.

Artificial intelligence technologies have been used increasingly by the United Nations. Several research and development labs, including the Global Pulse Lab, the Jetson initiative by the UN High Commissioner for Refugees , UNICEFs Innovation Labs and the Centre for Humanitarian Data have focused their work on developing artificial intelligence solutions that would support the UNs mission, notably in terms of anticipating and responding to humanitarian crises.

United Nations agencies have also used biometric identification to manage humanitarian logistics and refugee claims. The UNHCR developed a biometrics database which contained the information of 7.1 million refugees. The World Food Program has also used biometric identification in aid distribution to refugees, coming under some criticism in 2019 for its use of this technology in Yemen.

In parallel, the United Nations has partnered with private companies that provide analytical services. A notable example is the World Food Programme, which in 2019 signed a contract worth US$45 million with Palantir, an American firm specializing in data collection and artificial intelligence modelling.

In 2014, the United States Bureau of Immigration and Customs Enforcement (ICE) awarded a US$20 billion-dollar contract to Palantir to track undocumented immigrants in the U.S., especially family members of children who had crossed the border alone. Several human rights watchdogs, including Amnesty International, have raised concerns about Palantir for human rights violations.

Like most AI initiatives developed in recent years, this work has happened largely without regulatory oversight. There have been many attempts to set up ethical modes of operation, such as the Office for the Co-ordination of Humanitarian Affairs Peer Review Framework, which sets out a method for overseeing the technical development and implementation of AI models.

In the absence of regulation, however, tools such as these, without legal backing, are merely best practices with no means of enforcement.

In the European Commissions AI regulation proposal, developers of high-risk systems must go through an authorization process before going to market, just like a new drug or car. They are required to put together a detailed package before the AI is available for use, involving a description of the models and data used, along with an explanation of how accuracy, privacy and discriminatory impacts will be addressed.

The AI applications in question include biometric identification, categorization and evaluation of the eligibility of people for public assistance benefits and services. They may also be used to dispatch of emergency first response services all of these are current uses of AI by the United Nations.

Conversely, the lack of regulation at the United Nations can be considered a challenge for agencies seeking to adopt more effective and novel technologies. As such, many systems seem to have been developed and later abandoned without being integrated into actual decision-making systems.

An example of this is the Jetson tool, which was developed by UNHCR to predict the arrival of internally displaced persons to refugee camps in Somalia. The tool does not appear to have been updated since 2019, and seems unlikely to transition into the humanitarian organizations operations. Unless, that is, it can be properly certified by a new regulatory system.

Trust in AI is difficult to obtain, particularly in United Nations work, which is highly political and affects very vulnerable populations. The onus has largely been on data scientists to develop the credibility of their tools.

A regulatory framework like the one proposed by the European Commission would take the pressure off data scientists in the humanitarian sector to individually justify their activities. Instead, agencies or research labs who wanted to develop an AI solution would work within a regulated system with built-in accountability. This would produce more effective, safer and more just applications and uses of AI technology.

Read this article:
The United Nations needs to start regulating the 'Wild West' of artificial intelligence - The Conversation CA

Artificial Intelligence Technology Solutions, Inc., (OTCPK:AITX), a global leader in AI-driven security and productivity solutions for enterprise clients, filed its annual report on Form 10-K with the Securities and Exchange Commission for its fiscal year 2021 ended February 28, 2021. AITX is a full SEC reporting company that files detailed annual and quarterly reports.

"I am so pleased to share the results of such a pivotal year for the company," said Steve Reinharz, President and CEO of AITX. "The company has experienced significant improvement in all areas, and the financial state of AITX has never been stronger."

Key takeaways from the 10-K filing

Differences in Derivative Liability

The amount of derivative liability is a function of the underlying value of convertible debt and associated interest which reduced from to approximately $9,521,000 at February 29, 2020 to $943,000 at February 28, 2021 due to conversions and debt settlements and exchanges during the year and the change in fair value of derivative liabilities which fluctuates based on the change in the market price of the company's common stock. AITX therefore saw a reduction in derivative liability from $6,890,688 at February 29, 2020 to $446,466 at February 28, 2021.

Debt Exchange & New Financing at Market Price

In December of 2020, the company announced that it had exchanged approximately $7.7 M of current convertible debt and interest which had conversion rights at a conversion price discount of approximately 50% and whose debt bore interest at a default rate of 24% for $7.7 M in promissory notes along with warrants. The new debt has three year terms and bears interest at 12%. The company extended payment terms, improved interest rates, removed the associated derivative liability and stress on market price due to high volume discounted conversions. The company also issued $825,000 in new convertible debt that converts at market price and not the highly discounted conversion price that was done before. Reinharz added "Cleaning up this debt is a big deal!"

Story continues

"FY 2021 was just incredible for AITX," Reinharz added. "We couldnt have achieved this level of success without the tireless efforts of the entire team. From engineering to sales to production, every member contributed to this growth. We are well underway in a significant phase of growth and we expect to increase our recurring monthly revenue run rate by a factor 5 - 20 times when compared to the monthly revenue run rate at the end of next fiscal year ending February 28, 2022," Reinharz commented.

Reinharz also indicated that the company expects to release its first quarterly report that will cover March, April and May (the 10-Q) as soon as available as it will show substantial progress over the FY 2021 10-K in terms of revenue, debt and cash. "We are on track for an amazing year. Hold on, its early," Reinharz concluded.

Follow Steve Reinharz on Twitter @SteveReinharz for future AITX and RAD updates.

AITX through its subsidiary, Robotic Assistance Devices, Inc. (RAD), is redefining the $25 billion (US) security and guarding services industry through its broad lineup of innovative, AI-driven Solutions-as-a-Service business model. RAD solutions are specifically designed to provide a cost savings to businesses of between 35%-80% when compared to the industrys existing and costly manned security guarding and monitoring model. RAD delivers this tremendous costs savings via a suite of stationary and mobile robotic solutions that complement, and at times, directly replace the need for human personnel in environments better suited for machines. All RAD technologies, AI-based analytics and software platforms are developed in-house.

CAUTIONARY DISCLOSURE ABOUT FORWARD-LOOKING STATEMENTS

This release contains "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E the Securities Exchange Act of 1934, as amended and such forward-looking statements are made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. Statements in this news release other than statements of historical fact are "forward-looking statements" that are based on current expectations and assumptions. Forward-looking statements involve risks and uncertainties that could cause actual results to differ materially from those expressed or implied by the statements, including, but not limited to, the following: the ability of Artificial Intelligence Technology Solutions to provide for its obligations, to provide working capital needs from operating revenues, to obtain additional financing needed for any future acquisitions, to meet competitive challenges and technological changes, to meet business and financial goals including projections and forecasts, and other risks. Artificial Intelligence Technology Solutions undertakes no duty to update any forward-looking statement(s) and/or to confirm the statement(s) to actual results or changes in Artificial Intelligence Technology Solutions expectations.

About Artificial Intelligence Technology Solutions (AITX)

AITX is an innovator in the delivery of artificial intelligence-based solutions that empower organizations to gain new insight, solve complex challenges and fuel new business ideas. Through its next-generation robotic product offerings, AITXs RAD and RAD-M companies help organizations streamline operations, increase ROI and strengthen business. AITX technology improves the simplicity and economics of patrolling and guard services, and allows experienced personnel to focus on more strategic tasks. Customers augment the capabilities of existing staffs and gain higher levels of situational awareness, all at drastically reduced cost. AITX solutions are well suited for use in multiple industries such as enterprises, government, transportation, critical infrastructure, education and healthcare. To learn more, visit http://www.aitx.ai and http://www.roboticassistancedevices.com, or follow Steve Reinharz on Twitter @SteveReinharz.

View source version on businesswire.com: https://www.businesswire.com/news/home/20210601005345/en/

Contacts

Investor Relations ContactThe Waypoint Refinery, LLC845-397-2956www.thewaypointrefinery.com

Steve Reinharz949-636-7060

Read more here:
Artificial Intelligence Technology Solutions Files 10-K and Audited Financials - Yahoo Finance

Who hasn't been stuck seething at an interminable red light with zero cross traffic? When this happened one time too many to Uriel Katz, he co-founded Israel-based, Palo Alto, California-headquartered tech startup NoTraffic in 2017. The company claims its cloud- and artificial-intelligence-based traffic control system can halve rush-hour times in dense urban areas, reduce annual CO2 emissions by a half-billion tons in places like Phoenix/Maricopa County, and slash transportation budgets by 70 percent. That sounded mighty free-lunchy, so I got NoTraffic's VP of strategic partnerships, Tom Cooper, on the phone.

Here's how it works: Sensors perceive, identify, and analyze all traffic approaching each intersection, sharing data to the cloud. Here light timing and traffic flow is adjusted continuously, prioritizing commuting patterns, emergency and evacuation traffic, a temporary parade of bicycleswhatever. Judicious allocation of "green time" means no green or walk-signal time gets wasted.

I assumed such features had long since evolved from the tape-drive traffic control system Michael Cain's team sabotaged in Rome to pull off The Italian Job in 1969. Turns out that while most such systems' electronics have evolved, their central intelligence and situational adaptability have not.

Intersections that employ traffic-sensing pavement loops, video cameras, or devices that enable emergency vehicle prioritization still typically rely on hourly traffic-flow predictions for timing. When legacy system suppliers like Siemens offer similar technology with centralized control, it typically requires costly installation of fiber-optic or other wired-network connections, as the latency inherent in cellular communications can't meet stringent standards set by Advance Transportation Controller (ATC), National Electrical Manufacturers Association (NEMA), CalTrans, and others for safety and conflict resolution.

By contrast, NoTraffic localizes all the safety-critical decision-making at the intersection, with a camera/radar sensor that can identify vehicles, pedestrians, and bikers observing each approach. These sensors are wired to a box inside the existing control cabinet that can also accept input signals from pressure loops or other existing infrastructure. The controller only requires AC power. It connects to the cloud via 4G/5G/LTE, but this connection merely allows for sharing of data that constantly tailors the signal timing of nearby intersections. This is not nano-second, fiber-optic-speed critical info. NoTraffic promises to instantly leapfrog legacy intersections to state-of-the-art intelligence, safety sensing, and connectivity.

Installation cost per intersection roughly equals the cost budgeted for maintaining and repairing today's inductive loops and camera intersections every five years, but the NoTraffic gear allegedly lasts longer and is upgradable over the air. This accounts for that 70 percent cost savings.

NoTraffic's congestion-reduction claims don't require vehicle-to-infrastructure communications or Waze/Google/Apple Maps integration, but adding such features via over-the-air upgrades promises to further improve future traffic flow.

Hardening the system against Italian Job-like traffic system hacks is essential, so each control box is electrically isolated and firewalled. All input signals from the local sensors are fully encrypted. Ditto all cloud communications.

NoTraffic gear is up and running in California, Arizona, and on the East Coast, and the company plans to be in 41 markets by the end of 2021. Maricopa County has the greatest number of NoTraffic intersections, and projections indicate equipping all 4,000 signals in the area would save 7.8 centuries of wasted commuting time per year, valued at $1.2 billion in economic impact. Reducing that much idling time would save 531,929 tons of CO2 emissionsakin to taking 115,647 combustion-engine vehicles off the road. The company targets jurisdictions covering 80 percent of the nation's 320,000 traffic signals, noting that converting the entire U.S. traffic system could reduce CO2 by as much as removing 20 million combustion vehicles each year.

I fret that despite its obvious advantages, greedy municipalities might push to leverage NoTraffic cameras for red light enforcement, but Cooper noted the company's clients are traffic operations departments, which are not tasked with revenue generation. NoTraffic is neither conceived nor enabled to be an enforcement tool. Let's hope the system proves equally hackproof to government "revenuers" and gold thieves alike.

Read the original:
How Artificial Intelligence Is Cutting Wait Time at Red Lights - Motor Trend

Artificial intelligence must be the future for network security, according to Fortinet.

With the threat landscape constantly evolving and increasing in complexity, continued digital innovation, technological developments, and the introduction of 5G, coupled with the challenges of accelerated remote working practices and a growing cybersecurity skills gap, have collectively exacerbated the challenges that CISOs face in terms of protecting their companies digital assets.

As CISOs assess their cybersecurity posture, its essential that they consider how to leverage new and emerging technologies to best protect their infrastructure, the company says.

There have been significant developments in the artificial intelligence (AI) space that make it an increasingly strategic investment.

However, Fortinet says it can be challenging for CISOs to cut through the hype and understand which AI-based solution is best suited to their organisation.

The continued investment in digital innovation and development is one of the key factors in maintaining an advantage over competitors," says Corne Mare, chief information security officer, Fortinet.

"AI-driven solutions have been commonplace for some time now but determining which solution is best for an organisation can still be a hurdle for many CISOs."

Mare says it is not enough to simply incorporate AI-driven solutions into a security strategy.

"CISOs must also be able to assess the company behind the solution and ensure it has the appropriate knowledge, skills, and resources to operationalise it.

"Adequate access to actionable threat intelligence is equally critical. Its easy for technology companies to promote their AI solutions and claim they are AI-driven," Mare says.

"CISOs should only engage companies that can strongly back up these claims and demonstrate proven experience to provide the best defence and strategy for their organisation.

AI-driven solutions on their own may not be effective enough to secure an organisational environment. However, enhancing AI solutions with machine learning, augmented intelligence, and analytics capabilities, among others, lets CISOs create a much stronger cybersecurity ecosystem for their organisation.

As technological advancements see AI-driven solutions increase in their capabilities and complexities, so too do the capabilities of cybercriminals," says Mare.

"To reinforce a robust cybersecurity ecosystem, CISOs must develop strategic, proactive cybersecurity approaches that leverage AI-driven solutions to act on threat intelligence.

"Integrating other smart, digital solutions will help to deliver timely, accurate information that organisations can use to help prepare and protect their assets.

In addition to leveraging solutions like augmented intelligence, analytics, and machine learning combined with AI, CISOs should consider resourcing their IT and security teams with the right people to strengthen their security strategy.

However, there are also opportunities for CISOs to leverage their AI-driven security solutions to close the cybersecurity skills gap and mitigate resourcing challenges.

Developing a robust cybersecurity posture for an organisation often requires investing in a wide variety of technologies and tools to defend against threats," says Mare.

"While IT is a very skilled workforce, employees can be stretched thin in organisations trying to manage a large volume of digital solutions in addition to their daily responsibilities.

"However, CISOs can improve efficiencies and strengthen their security operations by leveraging AI solutions and tools, particularly those with built-in automation and integration, to alleviate the pressure on IT teams without reducing the effectiveness of the security strategy.

See original here:
Is artificial intelligence the future of network security? - SecurityBrief Asia

Atos and Thales have announced the creation of Athea, a joint-venture that will develop a sovereign Big Data and Artificial Intelligence platform for public and private sector players in the defence, intelligence and internal state security communities. Athea will draw on the experience gained by both companies from the demonstration phase of the ARTEMIS programme, the Big Data platform of the French Ministry of Armed Forces. The contract to optimise and prepare the full-scale roll-out of the ARTEMIS platform was also awarded jointly to the two leaders by the French Defence Procurement Agency on April 30, 2021. The new joint venture will initially serve the French market before addressing European requirements at a later date.

With the exponential rise in the number of sources of information and increased pressure to respond more quickly to potential issues, state agencies need to manage ever-greater volumes of heterogeneous data and accelerate the development of new AI applications where security and sovereignty are key. Athea will create a solution to securely handle sensitive data on a nationwide scale and support the implementation of that solution within government programmes. The new entity will also provide expert appraisal, consulting, training and other services.

The joint venture will pool the companies investments, expertise and experience to respond quickly and efficiently to demand for innovation. Athea will work with an ecosystem of large companies, SMEs, start-ups and research institutes specialising in Big Data and Artificial Intelligence. In conjunction with the recently created Defence Digital Agency, the joint entity will also provide secure solutions and open and modular technological building blocks, which encourage collaboration and stimulate the industrial and sovereign ecosystem, in order to support the development of trusted applications.

This joint venture between Thales and Atos illustrates the commitment of both our companies to supporting the Digital Transformation of our customers by providing a secure and innovative solution based on French technology to process huge volumes of heterogeneous data. Together, we will capitalise on our respective areas of expertise to provide best-in-class Big Data and Artificial Intelligence solutions, said Marc Darmon, Executive Vice President, Secure Communications and Information Systems, Thales.

Sensitive data capabilities have become a sovereignty issue for State agencies. By combining the expertise of two major players in defence and digital technologies with the flexibility of a dedicated entity, Athea will generate huge potential for innovation and stimulate the industrial and defence ecosystem, including innovative start-ups, to meet the needs of government agencies and other stakeholders in the sector. This new joint venture between Atos and Thales is an opportunity to combine a comprehensive understanding of the defence and security issues faced by European States with access to the latest innovations in Big Data and Artificial Intelligence, said Pierre Barnab, Senior Executive Vice President, Big Data and Cybersecurity, Atos.

Facebook Twitter LinkedInEmailWhatsApp

Read the original:
Thales and Atos create a sovereign Big Data and Artificial Intelligence platform - Intelligent CIO ME