6 developments in autonomous tech, coming soon
As more industries find themselves searching for viable solutions to common problems, they look towards automation. The concept of artificial intelligence (AI) has evolved over the years, and new applications for automation are emerging. It seems as though the world is moving towards automation rapidly, and industries will need to adopt this technology to stay ahead of the competition.
Continue reading to learn more about six autonomous technologies being developed that will change the way industries operate. They will contribute to higher levels of efficiency and productivity by complementing existing technologies.
Banks speed up their AI adoption to combat money laundering
A third of financial institutions are accelerating their AI and machine learning adoption for anti-money laundering (AML) technology in response to COVID-19.
Meanwhile, another 39 percent of compliance professionals say their AI/ML adoption plans will continue, despite the pandemic's disruption, this is according to a new study by analytics company SAS, consultancy KPMG and the Association of Certified Anti-Money Laundering Specialists (ACAMS).
Why AI isn't the only answer to cybersecurity [Q&A]
Read about any new cybersecurity product today and the chances are that it will be keen to stress its use of AI in some form.
But are we expecting too much from AI and are companies adopting it just because it's on trend? We spoke to Nadav Arbel, co-founder and CEO of managed SOC platform CYREBRO, to find out more about AI's role and why the human factor is still important.
Top industries on which AI and ML will have the greatest impact
Artificial intelligence (AI) and machine learning (ML) have been two of the most disruptive technological advancements of the past several years.
Gartner predicts that by 2024, 75 percent of enterprises have shifted from AI pilot stage implementation to operationalization. Their effects have been wide-ranging and promise to continue into the foreseeable future. Businesses will gain a substantial competitive advantage by capitalizing on the benefits of AI and ML.
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Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference.
With Machine Learning for Cybersecurity Cookbook you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers.
New reporting tools help manage machine learning risks
Machine learning operations and management software specialist Algorithmia is launching new, advanced reporting tools to help enterprises govern the use of ML models in production environments.
The top ML challenge currently facing organizations is governance according to the company's recent machine learning trends survey. This found 56 percent of IT leaders rank governance, security and auditability issues as a major concern.
New SaaS solution uses machine learning to detect cyber threats
Cybersecurity and risk management company RSA is launching Detect AI, a cloud-native advanced analytics and machine learning solution that provides rapid detection and actionable insights on data captured by the RSA NetWitness Platform.
It employs cloud-scale processing for behavior analytics and uses unsupervised machine-learning to allow it to detect and respond to threats without manual oversight.
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As machine learning algorithms become popular, new tools that optimize these algorithms are also being developed.
Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem.
10 emerging technologies in 2021
Despite an inarguably terrible year and many concerning events happening around the world -- pandemic notwithstanding -- technology is still advancing at breakneck speeds. That looks to continue well into the coming year, with many fascinating and emergent solutions bubbling to the surface.
Here are 10 emerging technologies everyone should be on the lookout for in 2021:
Democratization, ethics and data poisoning -- AI and ML predictions for 2021
In the second of our series of pieces looking at technology predictions for 2021 we look at the field of AI and machine learning.
This has the potential to impact on many areas of commerce, science and digital transformation, but what do industry experts think?
Enterprises ramp up AI/ML spending despite deployment challenges
In response to the economic impact of COVID-19 companies are turning to their investments in AI to deliver both short-term cost-cutting and long-term technology innovation to drive revenue and efficiency.
A report from ML operations and management software specialist Algorithmia finds that 83 percent of organizations have increased their budgets for AI/ML and that the average number of data scientists employed has increased 76 percent year-on-year.
New marketplace aims to promote transparency in AI and machine learning
The major challenges faced by businesses looking to implement AI and machine learning include transparency, bias, and quality of training data.
Swedish startup Unbiased is launching a new Data Marketplace on the Telos blockchain platform, aimed at providing privacy-centric and decentralized development tools to companies working with AI and Machine Learning applications.
BullGuard launches new anti-malware range with machine learning and multi-layer protection
BullGuard has announced its new 2021 security suite, featuring Dynamic Machine Learning, which continuously monitors all processes on a user's device, enabling real-time detection and blocking of potentially malicious behavior before it can do damage.
The new suite also offers Multi-Layered Protection which uses six layers -- Safe Browsing, Dynamic Machine Learning, Sentry Protection for Zero-Day Malware, an On-Access AV Engine, a Firewall and a Vulnerability Scanner -- to defend the user’s devices from malware, without the need for user interaction.
Pandemic provides boost to AI and ML adoption
Companies are planning to increase their spending on AI/ML as a result of the pandemic, and many have realized that those initiatives should have been a higher priority for their organizations all along.
A new survey of enterprise IT leaders from Algorithmia, a provider of ML operations and management solutions, shows that 91 percent of respondents were spending at least $1,000,000 annually on AI/ML prior to the pandemic, and 50 percent say they are planning to spend more than that going forward.
How machine learning is changing digital marketing [Q&A]
Increasingly customers expect personalized experiences that are relevant to their unique situations and needs. However, with the increased reliance on technology needed to provide this, the human angle can go by the board.
We spoke to Jon Perera, CMO at sales and marketing software specialist Highspot to learn more about how people, processes and technology can be aligned to offer optimum customer experience.
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