Since its debut in November, ChatGPT has become the internet's new favorite plaything. The AI-driven natural language processing tool rapidly amassed more than 1 million users, who have used the web-based chatbot for everything from generating wedding speeches and hip-hop lyrics to crafting academic essays and writing computer code. Not only have ChatGPT's human-like abilities taken the internet by storm, but it has also set a number of industries on edge: a New York school banned ChatGPT over fears that it could be used to cheat, copywriters are already being replaced, and reports claim Google is so alarmed by ChatGPT's capabilities that it issued a "code red" to ensure the survival of the company's search business. It appears the cybersecurity industry, a community that has long been skeptical about the potential implications of modern AI, is also taking notice amid concerns that ChatGPT could be abused by hackers with limited resources and zero technical knowledge. Just weeks after ChatGPT debuted, Israeli cybersecurity company Check Point demonstrated how the web-based chatbot, when used in tandem with OpenAI's code-writing system Codex, could create a phishing email capable of carrying a malicious payload. Check Point threat intelligence group manager Sergey Shykevich told TechCrunch that he believes use cases like this illustrate that ChatGPT has the "potential to significantly alter the cyber threat landscape," adding that it represents "another step forward in the dangerous evolution of increasingly sophisticated and effective cyber capabilities."

He also fears that the advancement of machine learning and artificial intelligence to fight potential cybercrime is similarly being used by …

The evolution of cloud computing and artificial intelligence are growing in parallel, and the complexity of the cloud is driving the need for AI. In addition, the complexity of AI is also creating the need for it to work better in the cloud environment with efficiency, transparency and control. Organizations are taking a more data-driven approach, where artificial intelligence can be used to detect and proactively provide alerts on weaknesses and vulnerabilities both that are being exploited right now, or that might be exploited in the future. This is being done by analyzing data coming in and out of protected endpoints, both detecting threats based on known behavior, and spotting yet known threats based on predictive analytics. Join this interactive presentation and be sure to stick around for Q&A with Melvin!

In recent years, homeowners have adopted smart home technologies to improve their quality of life. Connected devices and appliances perform actions, tasks, and automated routines based on a homeowner's preferences. Smart technologies enable homeowners to save time, money, and energy. Major tech companies such as Apple, Google, and Amazon have driven the adoption of smart home technologies. From digital voice assistants to intelligent thermostats and everything in between, smart homes are the homes of the future.

People have embraced machine learning in different industries and sectors. Cybersecurity is one sector that has significantly benefited from it, thanks to its wide range of applications. It has helped solve some of the most common cybersecurity problems that individuals and businesses experience. Practical solutions are in high demand in an era where cybersecurity threats are soaring. Machine learning has proven to make threat detection and prediction easier.

Whether you are just overwhelmed with data or just curious about what you will learn, you may be feeling the impulse to jump on the artificial intelligence (AI) bandwagon. Before you go too far down the road, please consider this Top 10 list of the most common mistakes mangers make when building an AI project. This comes from long, hard lessons learned across multiple missions and IT clients over the years. Mission owners have a lot to do. It is usually the most annoying or time-intensive tasks they want to automate the most. I never begrudge someone who is trying to better optimize the cognitive talent of their team.

The strategic combination of a Defensive Artificial Intelligence implementation collaborated with Robotic Process Automation strategies to bring an adaptive, effective, and buzz-worthy edge to the industry.

In October, we included NATO's release of its first-ever strategy for artificial intelligence in the OODA Loop Daily Pulse. The strategy is primarily concerned with the impact AI will have on the NATO core commitments of collective defense, crisis management, and cooperative security. Worth a deeper dive is a framework within the overall NATO AI Strategy, which mirrors that of the DoD Joint Artificial Intelligence Center's (JAIC) and other U.S.-based efforts to establish norms around AI: "NATO establishes standards of responsible use of AI technologies, in accordance with international law and NATO's values." At the center of the NATO AI strategy are the "NATO Principles of Responsible Use of Artificial Intelligence in Defence," which are based on the NATO and Allies commitment to "ensuring that the AI applications they develop and consider for deployment will be – at the various stages of their lifecycles – in accordance with the following six principles: Lawfulness, Responsibility and Accountability, Explainability and Traceability, Reliability, Governability, and Bias Mitigation." OODA Loop provides actionable intelligence, analysis, and insight on global security, technology, and business issues.

I most appreciate AI when it augments human work and makes us stronger or more effective; when it performs tasks that we do not want to do or struggle to do, thereby freeing us to enjoy the activities we are good at and like. Remember how the introduction of the electronic spreadsheet did not make accountants or statisticians obsolete but instead gave them numerical "super-powers" that made their work easier and better? But what is critical is that companies and consumers understand how an AI algorithm uses data to make better decisions that protect all stakeholders from disappointment and harm. This means AI's decision-making process must be transparent to reinforce trust, fair to avoid bias, protective of data to ensure privacy, and vigilant against cybersecurity threats to prevent external abuse. As well as having negative implications for the consumer, the possible harm of misuse of data by AI can tarnish a company's brand, stripping away the trust that it has worked so hard to build over the years.

Artificial Intelligence (AI) is the faculty of a computer system to learn and reason, therefore, mimicking human intelligence. Over the course of the past several years, AI has become an indispensable part of cybersecurity measures. AI can predict cyberattacks with matchless precision, helps to create better security features that can bring down the number of cyberattacks and mitigate its impact on IT infrastructure. Artificial intelligence is a powerful cybersecurity tool for enterprises. It is rapidly turning into a sophisticated protective gear for enterprise cybersecurity, and many enterprises are adopting it at a rapid pace. Statista, in a recent post, noted that in 2019 approximately 83% of organizations based in the United States consider that without AI, their organization fails to deal with cyberattacks.