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Artificial Intelligence: Technology Trends

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As artificial intelligence (AI) becomes more pervasive and embedded in life-changing decisions, the need for transparency has intensified. There have been plenty of high-profile cases in recent years where AI has contributed to bias and discrimination, with the use of facial recognition for policing just one example. There is a high probability of a shift from loose self-regulation to government involvement in AI over the next couple of years. In turn, Big Tech is increasingly using AI to solve the privacy and bias problems that the technology itself created. Listed below are the key technology trends impacting the AI theme, as identified by GlobalData.


Unstructured Privacy Data Risks: AI Can Help

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As per Gartner, 65% of world population's data will be impacted due to privacy regulations by 2023. In fact, it might happen sooner as most countries wish to provide economic nationalism by restricting cross country data transfers and data rationing by global technology businesses. Another Independent trend coupled with the rise of tighter privacy regulations is the volume of unstructured data being collected. Combined, both structured & unstructured data are projected to grow at the rate of 7-12% on an annual basis. Technological advances along with ever falling storage prices have made it quite easy to collect unstructured data from the customers.


Musk says Tesla would be shut down if cars used for spying

The Japan Times

Tesla Inc. Chief Executive Officer Elon Musk used an opportunity to speak to an audience in China to strenuously deny the electric carmaker would ever use a vehicle's technology for spying. Appearing on Saturday at the China Development Forum, a conference organized by a unit of the country's State Council, in a session titled: The Next Disruptive Innovation?, Musk said that if Tesla ever used its cars to spy in China, or anywhere, we would get "shut down everywhere." "If a commercial company did engage in spying, the negative effects to that company would be extremely bad," said Musk, who was beamed in remotely from America, where it was late in the evening. "For example, if Telsa used the cars to spy in China -- or anywhere, any country -- we will get shut down everywhere. So there's a very strong incentive for us to be very confidential with any information."


Why Supply Chains Are Today's Fastest Growing Cybersecurity Threat - Security Boulevard

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Language EnglishTags:  Business ecosystems have expanded over the years owing to the many benefits of diverse, interconnected supply chains, prompting organizations to pursue close, collaborative relationships with their suppliers. However, this has led to increased cyber threats when organizations expose their networks to their supply chain and it only takes one supplier to have cybersecurity vulnerabilities to bring a business to its knees. To this point governments around the world have highlighted supply chains as an area for urgent attention in tackling cyber risk in the coming years. Looking Beyond Your Own Perimeter Over the last few years, many organizations have worked hard to improve their cyber defenses and are increasingly ‘harder targets’. However, for these well-defended organizations, now the greatest weaknesses in their defenses are their suppliers, who are typically less well defended but with whom they are highly interconnected. At the same time, the cyber threat landscape has intensified, and events of the past year have meant that security professionals are not only having to manage security in a remote working set up and ensure employees have good accessibility, they are also having to handle a multitude of issues from a distance while defending a much broader attack surface. As a result, points of vulnerability have become even more numerous, providing an attractive space for bad actors to disrupt and extort enterprises. Threats have escalated, including phishing and new variants of known threats, such as ransomware and Denial of Service (DDoS) attacks, as well as increases in supply chain attacks. But where supply chains are concerned, it is nearly impossible to effectively manage this risk unless you know the state of your suppliers’ defenses and continually ensure that they are comparable to your own. Organizations must deeply understand the cyber risks associated with the relationship and try to mitigate those risks to the degree possible. However, that’s easier said than done. With the sending and receiving of information essential for the supply chain to function, the only option is to better identify and manage the risks presented. This requires organizations to overhaul existing risk monitoring programs, technology investments and also to prioritize cyber and data security governance. Ensuring the Basics are in Place At the very least organizations should ensure that both they and their suppliers have the basic controls in place such as Cyber Essentials, NIST and ISO 27001, coupled with good data management controls. They should thoroughly vet and continuously monitor supply chain partners. They need to understand what data partners will need access to and why, and ultimately what level of risk this poses. Likewise, they need to understand what controls suppliers have in place to safeguard data and protect against incoming and outgoing cyber threats. This needs to be monitored, logged, and regularly reviewed and a baseline of normal activities between the organization and the supplier should be established. As well as effective processes, people play a key role in helping to minimize risk. Cybersecurity training should be given so that employees are aware of the dangers and know how to spot suspicious activity. They should be aware of data regulation requirements and understand what data can be shared with whom. And they should also know exactly what to do in the event of a breach, so a detailed incident response plan should be shared and regularly reviewed. IT best practices should be applied to minimize these risks. IT used effectively can automatically protect sensitive data so that when employees inevitably make mistakes, technology is there to safeguard the organization. Securely Transferring Information Between Suppliers So how do organizations transfer information between suppliers securely and how do they ensure that only authorized suppliers receive sensitive data? Here data classification tools are critical to ensure that sensitive data is appropriately treated, stored, and disposed of during its lifetime in accordance with its importance to the organization. Through appropriate classification, using visual labelling and metadata application to emails and documents, this protects the organization from the risk of sensitive data being exposed to unauthorized organizations further down the line through the supply chain. Likewise, data that isn’t properly encrypted in transit can be at risk of compromise, so using a secure and compliant mechanism for transferring data within the supply chain will significantly reduce risks. Managed File Transfer (MFT) software facilitates the automated sharing of data with suppliers. This secure channel provides a central platform for information exchanges and offers audit trails, user access controls, and other file transfer protections. Layering Security Defenses Organizations should also layer security defenses to neutralize any threats coming from a supplier. Due to its ubiquity, email is a particularly vulnerable channel and one that’s often exploited by cyber criminals posing as a trusted partner. Therefore, it is essential that organizations are adequately protected from incoming malware, embedded Advanced Persistent Threats, or any other threat that could pose a risk to the business. And finally, organizations need to ensure that documents uploaded and downloaded from the web are thoroughly analyzed, even if they are coming from a trusted source. To do this effectively, they need a solution that can remove risks from email, web and endpoints, yet still allows the transfer of information to occur. Adaptive Data Loss Prevention (DLP) allows the flow of information to continue while removing threats, protecting critical data, and ensuring compliance. It doesn’t become a barrier to business or impose a heavy management burden. This is important because traditional DLP ‘stop and block’ approaches have often resulted in too many delays to legitimate business communications and high management overheads associated with false positives. Cyber Criminal Attacks Set to Rise Many of the recent well publicized attacks have been nation state orchestrated. Going forward this is going to turn into criminal syndicate attacks. Cyber criminals already have the ransomware capabilities and now all they need to do is tie this up with targeting the supply chain. Therefore, making sure you have the right technologies, policies and training programs in place should be a top priority for organizations in 2021. If you are interested in finding out more about protecting your supply chain, download our Guide: “Managing Cybersecurity Risk in the Supply Chain.” Download the Guide Additional Resources On-Demand Webinar: Managing the Cybersecurity Supply Chain Risk in File TransfersTags: Featured: 1


Google is investigating an AI researcher over the handling of sensitive data

Engadget

Google is investigating an artificial intelligence researcher after it detected that "an account had exfiltrated thousands of files" and shared them externally. Margaret Mitchell, a co-lead of the Ethical AI unit, has been locked out of Google's corporate systems over the matter. But apparently they've told her she will be locked out for at least a few days. The investigation follows the acrimonious exit last month of another prominent AI researcher, Timnit Gebru, who said Mitchell has been told that she'll be locked out for a few days. According to an Axios source, Mitchell used automated scripts to search her messages for examples of discriminatory treatment toward Gebru.


Confidential computing: the final frontier of data security

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Data threats never rest, nor should the protection of your sensitive information. That's the driving principle behind confidential computing, which seeks to plug a potentially crippling hole in data security. Confidential computing provides a secure platform for multiple parties to combine, analyze and learn from sensitive data without exposing their data or machine learning algorithms to the other party. This technique goes by several names -- multiparty computing, federated learning and privacy-preserving analytics, among them -- and confidential computing can enable this type of collaboration while preserving privacy and regulatory compliance. Data exists in three states: in transit when it is moving through the network; at rest when stored; and in use as it's being processed.


The Challenges of Running Computer Vision on the Edge

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Artificial intelligence (AI) is the field of making computers able to act intelligently, to make decisions in real environments that will have favorable outcomes. This is obviously a broad, and somewhat vague, definition, and there are many fields within this umbrella term. One example of such a field is that of computer vision, in which computers can process images as a human would, and make inferences about what is in an image so that computer programs can then use that information to make decisions that have favorable outcomes. It is becoming more common to see artificial intelligence applications such as computer vision integrated into new business models and products. Computer vision has many real-world applications, analyzing traffic patterns, detecting changes in posture, counting the number of persons in an area, etc. Learning how to build any computer vision application requires a steep learning curve, and deploying it to the edge adds an extra layer of complication.


insideBIGDATA Latest News – 11/10/2020 - insideBIGDATA

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In this regular column, we'll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we're in close touch with vendors from this vast ecosystem, so we're in a unique position to inform you about all that's new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive. Algorithmia, a leader in ML operations and management software, announced Insights, a new solution for ML model performance monitoring that provides reliable access to algorithm inference and operations metrics. Many organizations today don't have the ability to monitor the performance of ML models working their way into production applications, and organizations that do, use a patchwork of disparate tools and manual processes, often without critical data required to satisfy stakeholder requirements. Without comprehensive monitoring and centralized data collection, organizations struggle with model drift, risk of failure, and the inability to meet performance targets in response to shifts in environment and customer behavior.


6 Privacy Solutions for Big Data and Machine Learning

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Travelers who wander the banana pancake trail through Southeast Asia will all get roughly the same experience. They'll eat crummy food on one of fifty boats floating around Halong Bay, then head up to the highlands of Sapa for a faux cultural experience with hill tribes that grow dreadful cannabis. After that, it's on to Laos to float the river in Vang Vien while smashed on opium tea. Eventually, you'll see someone wearing a t-shirt with the classic slogan – "same same, but different." The origins of this phrase surround the Southeast Asian vendors who often respond to queries about the authenticity of fake goods they're selling with "same same, but different." It's a phrase that appropriately describes how the technology world loves to spin things as fresh and new when they've hardly changed at all.


6 Privacy Solutions for Big Data and Machine Learning

#artificialintelligence

Travelers who wander the banana pancake trail through Southeast Asia will all get roughly the same experience. They'll eat crummy food on one of fifty boats floating around Ha Long Bay, then head up to the highlands of Sa Pa for a faux cultural experience with hill tribes that grow dreadful cannabis. After that, it's on to Laos to float the river in Vang Vieng while smashed on opium tea. Eventually, you'll see someone wearing a t-shirt with the classic slogan – "same same, but different." The origins of this phrase surround the Southeast Asian vendors who often respond to queries about the authenticity of fake goods they're selling with "same same, but different." It's a phrase that appropriately describes how the technology world loves to spin things as fresh and new when they've hardly changed at all.