If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Smart-assistant devices have had their share of privacy missteps, but they're generally considered safe enough for most people. New research into vulnerabilities in Amazon's Alexa platform, though, highlights the importance of thinking about the personal data your smart assistant stores about you--and minimizing it as much as you can. Findings published on Thursday by the security firm Check Point reveal that Alexa's web services had bugs that a hacker could have exploited to grab a target's entire voice history, meaning their recorded audio interactions with Alexa. Amazon has patched the flaws, but the vulnerability could have also yielded profile information, including home address, as well as all of the "skills," or apps, the user had added for Alexa. An attacker could have even deleted an existing skill and installed a malicious one to grab more data after the initial attack.
This article explains how Machine Learning Operations came to be a discipline inside many companies and things to consider when deciding if your organization is ready to form an MLOps team. Machine learning (ML) is a subset of artificial intelligence in which computer systems autonomously learn a task over time. Based on pattern analyses and inference models, ML algorithms allow a computer system to adapt in real time as it is exposed to data and real-world interactions. For many people, ML was, until recently, considered science fiction. But advances in computational power, frictionless access to scalable cloud resources, and the exponential growth of data have fueled an increase in ML-based applications.
AI Daily Roundup starts today! We are covering the top updates from around the world. The updates will feature state-of-the-art capabilities in artificial intelligence, Machine Learning, Robotic Process Automation, Fintech and human-system interactions. We will cover the role of AI Daily Roundup and their application in various industries and daily lives. Bayard Bradford developed the Ultimate Data Export app as a result of participating in HubSpot's new App Accelerator program.
Mobile devices are popular with hackers because they're designed for quick responses based on minimal contextual information. Verizon's 2020 Data Breach Investigations Report (DBIR) found that hackers are succeeding with integrated email, SMS and link-based attacks across social media aimed at stealing passwords and privileged access credentials. And with a growing number of breaches originating on mobile devices according to Verizon's Mobile Security Index 2020, combined with 83% of all social media visits in the United States are on mobile devices according to Merkle's Digital Marketing Report Q4 2019, applying machine learning to harden mobile threat defense deserves to be on any CISOs' priority list today. Google's use of machine learning to thwart the skyrocketing number of phishing attacks occurring during the Covid-19 pandemic provides insights into the scale of these threats. During a typical week in April of this year, Google's G-Mail Security team saw 18M daily malware and phishing emails related to Covid-19.
The application of convolutional neural network technology continues to expand beyond machine vision use cases to the red-hot drug discovery market. The application of AI to new drug development has moved in fits and starts, including IBM's (NYSE: IBM) decision last year to pull the plug on its Watson AI software for pharmaceutical research. Lately, investors are warming to new small molecule drug discovery efforts, including recent efforts aimed at developing therapies for COVID-19. The latest example comes from Atomwise, a San Francisco-based company that claims to have developed the first convolutional neural network for new drug discovery. Atomwise announced a hefty $123 million Series B funding round this week, bringing its investment total to more than $174 million.
WekaIO (Weka), the innovation leader in high-performance and scalable file storage, and an NVIDIA Partner Network Solution Advisor introduced Weka AI, a transformative storage solution framework underpinned by the Weka File System (WekaFS) that enables accelerated edge-to-core-to-cloud data pipelines. Weka AI is a framework of customizable reference architectures (RAs) and software development kits (SDKs) with leading technology alliances like NVIDIA, Mellanox, and others in the Weka Innovation Network (WIN) . Weka AI enables chief data officers, data scientists and data engineers to accelerate genomics, medical imaging, the financial services industry (FSI), and advanced driver-assistance systems (ADAS) deep learning (DL) pipelines. In addition, Weka AI easily scales from entry to large integrated solutions provided through VARs and channel partners. Artificial Intelligence (AI) data pipelines are inherently different from traditional file-based IO applications.
The Stanford Center for Health Education has launched an online program on Artificial Intelligence in Healthcare. Designed for technology professionals, computer scientists, and healthcare providers, the program aims to advance the delivery of patient care and improve global health outcomes through artificial intelligence and machine learning. The online program will be taught by faculty from Stanford Medicine. The program's goal is to foster a common understanding of the potential for AI to safely and ethically improve patient care. "Effective use of AI in healthcare requires knowing more than just the algorithms and how they work," says Nigam Shah, associate professor of medicine and biomedical data science, the faculty director of the new program.
Origami Risk LLC and Gradient A.I. Corp. have formed a partnership allowing Gradient's claims and policy modeling capabilities and predictive analytics resources to be used on Origami's digital platform, the companies said in a joint release Tuesday. Insurers, third-party administrators, risk pools, and self-insured organizations will be able to access Gradient's proprietary data sets of millions of claims and policies, which are integrated with the Origami platform's workflow, reporting and digital engagement tools, the statement said. The Gradient tools can be applied to policy underwriting and claims adjusting processes, such as enabling claim teams to focus greater attention on claims with a high probability of becoming significant cost-drivers, the statement said. "Our collaboration with Gradient AI offers insurers, risk pools and large self-administered plans using our platform ready access to" Gradient's tools, Robert Petrie, CEO of Origami Risk, said in the statement.
Jumper.ai is an AI-based platform that enables brands and SME's to instantly auto-reply and engage with customers. Its platform features conversational commerce, live chat, automated replies, bot builder, and abandoned cart recovery. Boxx.ai is a Bengaluru based artificial intelligence startup that helps e-commerce companies increase their conversion rates by displaying the most personalised products for each user. Boxx.ai predicts what each visitor is likely to buy next using its proprietary algorithms. This helps consumer internet companies curate a line of products and extend a highly personalised experience to each of its customers.
Frameworks and libraries can be said as the fundamental building blocks when developers build software or applications. These tools help in opting out the repetitive tasks as well as reduce the amount of code that the developers need to write for a particular software. Recently, the Stack Overflow Developer Survey 2020 surveyed nearly 65,000 developers, where they voted their go-to tools and libraries. Here, we list down the top 12 frameworks and libraries from the survey that are most used by developers around the globe in 2020. About: Originally developed by researchers of Google Brain team, TensorFlow is an end-to-end open-source platform for machine learning.