- “Machine learning is a very powerful technique for security—it’s dynamic, while rules-based systems are very rigid,” says Dawn Song, a professor at the University of California at Berkeley’s Artificial Intelligence Research Lab. “It’s a very manual intensive process to change them, whereas machine learning is automated, dynamic and you can retrain it easily.”
- “We will see an improved ability to identify threats earlier in the attack cycle and thereby reduce the total amount of damage and more quickly restore systems to a desirable state,” says Amazon Chief Information Security Officer Stephen Schmidt.
- A Microsoft system designed to protect customers from fake logins had a 2.8 percent rate of false positives
- To do a better job of figuring out who is legit and who isn’t, Microsoft technology learns from the data of each company using it, customizing security to that client’s typical online behavior and history. Since rolling out the service, the company has managed to bring down the false positive rate to .001 percent. “
- “A study by Accenture has predicted that growth in the AI healthcare space is expected to touch $6.6 Bn by 2021 with a CAGR of 40%.
- A report by Juniper Research states that chatbots will be responsible for saving $8 Bn per annum of costs by 2022 for Retail, ecommerce, Banking, and Healthcare
- The same research study also predicts that the success of chatbot interactions where no human interventions take place will go up to 75% in 2022 from 12% in 2017.
- In 2017, Scanadu developed doc.ai. The application takes away one task from doctors and assigns it to the AI – the job of interpreting lab results.
- Medical image diagnosis is another AI use case in healthcare. One of the most significant issues that medical practitioners face is sifting through the volume of information available to them, thanks to EMRs and EHRs.
- Artificial Intelligence in Healthcare also talks about deep learning. Researchers are using deep learning to train machines to identify cancerous tissues with an accuracy comparable to a trained physicist.
- Machine learning in healthcare can help enhance the efforts in pathology often traditionally left to pathologists as they often have to evaluate multiple images in order to reach a diagnosis after finding any trace of abnormalities.
- Another similar solution is Moon developed by Diploid which enables early diagnosis of rare diseases through the software, allowing doctors to begin early treatment.
- Cybersecurity has become a significant concern for healthcare organizations, threatening to cost them $380 per patient record.
- The AiCure app developed by The National Institutes of Health helps monitor medication by a patient.”
“Hyderabad: Artificial Intelligence is getting good at doing bad things swiftly, evident from the alerts put out by leading cybersecurity companies that attackers won’t just target AI systems but will create AI techniques themselves to amplify their own criminal activities.
Although AI will help automate manual tasks, enhance decision-making and other human activities, it can attack many systems including AI.
Instead of hackers finding loopholes, AI itself can search for undiscovered vulnerabilities that it can exploit.
For instance it can be used to make phishing and other social engineering attacks even more sophisticated by creating extremely realistic video and audio or well-crafted emails designed to fool individuals. AI could also be used to launch disinformation campaigns.
Researchers have been rising increasingly concerned about the vulnerability of these artificially intelligent systems to malicious input that can corrupt their logic and affect their operations.
The World Economic Forum came out with a report, last week on Adversarial AI, cautioning governments: “Changes in the threat landscape are already apparent. Criminals are already harnessing automated reconnaissance, target exploitation and network penetration end-to-end”. Experts noted that attackers will be employing AI to avoid detection by security software and will even automate target selection, and check infected environments before deploying later stages and avoiding detection.
Chief technology officer, Symantec, Mr Hugh Thompson, said, ‘In some ways, the emergence of critical AI systems as attack targets will start to mirror the sequence seen 20 years ago with the internet, which rapidly drew the attention of cybercriminals and hackers, especially following the explosion of internet-based eCommerce. The fragility of some AI technologies will become a growing concern in 2019.'”
- “Data mining is not true AI (more about that in just a bit), but how it is used illustrates another important trend involving AI and ML: the correlation between a bank’s size and the sophistication of its learning systems, with larger banks typically using more sophisticated systems than smaller ones. When it comes to data mining, for instance, 95 percent of large banks and 79 percent of mid-sized banks use it, the report found. Meanwhile, just 61 percent of small banks reported using data mining technology — a majority, but not nearly as prevalent as it is among larger FIs.
- True AI systems, by contrast, are used by only 5.5 percent of financial institutions, as their interviews were used to help construct the report’s findings. Far more popular — besides data mining — were less sophisticated technologies, including BRMS, which enables companies to easily define, deploy, monitor and maintain new regulations, procedures, policies, market opportunities and workflows.”
“Our [technique] can be immensely helpful, as out of 284,807 samples we can safely rule out 139,220 [transactions],” they wrote.
If you’ve purchased or sold something on eBay recently, you might have encountered the system in action. The researchers coyly noted that it was successful in picking out fraudulent transactions in data from an “ecommerce platform”
“The ecommerce industry has seen tremendous growth in the last decade and it doesn’t look to slow down anytime soon.
2017 alone favored global retail e-commerce sales to the tune of 2.3 trillion dollars which is a trillion dollars extra to what it was in 2014. This figure is likely to grow by over 246% by 2021.
Blockchain, which is one of the most reformative technological inventions of the fourth industrial revolution has already disrupted several major sectors including the finance, health and gaming industries. It is further looking to have a major impact in ecommerce industry.”
“According to a recent study by Voicebot.ai, 47.3 million Americans, or nearly one in five, now have access to a smart speaker. That’s a lot of people asking voice assistants for directions, recipes, jokes, music and, increasingly, to make purchases. Of those 47 million who own smart speakers, 57% have made a purchase using that speaker.”
“Our own recent research showed 55% of shoppers said they like purchasing through voice-activated devices,” El-Arifi says.
“According to a recent study by ReportLinker, 31% of consumers list privacy concerns as the main drawback to owning a smart device. But at the same time, 90% of smart speaker owners wish their devices could do more, suggesting that the best way to stave off privacy concerns is to add value.”
“The cybersecurity market is now worth $120 billion, according to 2018 research, a roughly 13,500 percent increase compared to a decade earlier. What’s more, spending is expected to increase to $1 trillion by 2021 as companies invest in emerging prevention solutions. In fact, more are already turning to artificial intelligence, data analytics, machine learning and other technologies to strengthen their cybercrime defenses.
These technologies seem to hold promise in the fight against fraud, too, thanks to their ability to track and interpret massive amounts of data. This information can then be used to better understand what separates normal consumer behavior from that of bad actors, improving defenses, reducing false positives and giving consumers more convenient and secure online experiences.”