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BAE's Peder Jungck to Participate in GovCon Wire's National Security AI Innovation Forum

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Join the virtual forum to hear from government and commercial sector executives as they share insight on how AI technology is shaping the future of …



Baker McKenzie creates data and machine learning team, deepening AI partnership

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Building on a pilot partnership with an artificial intelligence company it launched last year, Baker McKenzie is upping its bet that machine learning and …


Hardening AI: Is machine learning the next infosec imperative?

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Alongside such attacks, we've seen new impetus behind the regulation of artificial intelligence (AI), with the world's first regulatory framework for the …


Report Highlights How AI Could Amplify Future Disinformation Campaigns

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A report released Wednesday outlines how impactful today's artificial intelligence and neural networks could be if programmed to automate disinformation campaigns. Conducted by Georgetown's Center for Security and Emerging Technology, the report studies how OpenAI's GPT-3--a powerful AI system that generates text based on prompts from humans--could automate the future generation of disinformation campaigns. Researchers looked into GPT-3's capabilities after it authored a September op-ed in The Guardian--the first article written entirely by AI. "If GPT-3 can write seemingly credible news stories, perhaps it can write compelling fake news stories; if it can draft op-eds, perhaps it can draft misleading tweets," the report states. "In light of this breakthrough, we consider a simple but important question: can automation generate content for disinformation campaigns?" Researchers evaluated GPT-3's performance on six tasks common to most disinformation campaigns, including the operation carried out by Russia's Internet Research Agency in 2016.


Explainability won't save AI

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Much of artificial intelligence, and particularly deep learning, is plagued by the … To promote human-machine interaction and enable partnership and …


2021 NLP Trends

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Listen to this episode from Tcast on Spotify. Voice recognition software is getting better and better. Once upon a time, it was something that was extremely clunky and unreliable and even the best systems required you to spend far too much time training them while speaking extremely slowly and enunciating like…well…like a computer. However, at last, the systems have improved to the point where it’s possible to at least accurately convey meaning through talk to text features without having to clarify every other word. In fact, I know a trucker who does most of his communication using talk to text on his phone. It makes a few mistakes here and there but its accuracy is still pretty impressive considering he’s speaking normally while in a large moving vehicle.  Then there are the voice assistants on our phones. Whether you talk to Siri, Alexa, or Cortana (all four of you, you know who you are) that voice recognition starts out needing a little training but nothing like it used to. And the more you use it to look up local restaurants, find a factoid to settle an argument or to book a hotel room, the more accurate it gets. Now, they are even in the homes of many, listening constantly for you to need their assistance with something – everything from dimming the lights to spinning up your favorite playlist on Spotify.  The improvements in this software hold a lot of potential. It has already been used for years in business to accommodate certain employees who may not be able to speak clearly or who lose the use of their arms. It is also a much more efficient way to record information than the increasingly dated keyboard. Typing is inherently inefficient, creating the possibility for misspellings that need to be corrected lest they convey an unintended meaning. It also requires a keyboard, which adds space, weight and money to your computer. As voice recognition software improves, the keyboard can be replaced with a simple microphone, probably the one on your phone. Imagine being able to compose reliable messages for business, a book, notes on a law case and have them all transcribed without having to take the time to proofread them. The time savings would be impressive. Or perhaps a more mundane situation in which you’re sitting at home and have a craving for pizza, but you can’t quite remember the name of the place you got it from last month. You throw the question out into the air and your device reminds you of the name, the price and asks you if you’d like it to order a pizza for you. If you think about it, Alexa and other smart devices are only a step or two away from that level of functionality. Another use would be in hospitals. Embedded microphones would record conversations with your doctor, highlighting the important points and recording all of the important information. This would save time and increase efficiency in a number of ways. No more would nurses and admins have to spend hours on data entry, with all the potential transcription errors that entail. Incidentally, that would also save you having to answer the same questions three times every time you go in for a checkup. It also means no one, or at least very few people have to come in contact with the Petri dishes known as keyboards in an environment that should be kept as sterile as possible.  Lectures and presentations could be recorded and transcribed instantly, making information readily available in real time. The possibilities are enormous. Yet, there are potential problems that arise, namely, who owns all that data getting generated and recorded? Is it the place where the recording happens? The place where they are stored? Some other party? At TARTLE, we believe all the data you generate is yours. So if it’s your information and your data that is being recorded, then you deserve to be the primary beneficiary of sharing it, or of deciding whether you want to share that data or not. These are questions that will be addressed sooner or later in the legislative realm which is why we are encouraging people to sign up at tartle.co to join the TARTLE movement. Together we can help steer that eventual legislation in a direction that will benefit not just a few, but each person who works to generate that data in the first place.  What’s your data worth? www.tartle.co


Virginia Girl Scouts use drones to deliver cookies and it pays off

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Drones and cookies apparently work well together. In April, Fox News reported that some Girl Scout troops across the country were having trouble with their cookie sales due to the pandemic. In Virginia, however, some members decided to try using drones to bring the popular cookies to customers.


The best text-generating AI models could turbocharge disinformation campaigns

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A new report lays out the ways that cutting-edge text-generating AI models could be used to aid disinformation campaigns. Why it matters: In the wrong hands text-generating systems could be used to scale up state-sponsored disinformation efforts -- and humans would struggle to know when they're being lied to. How it works: Text-generating models like OpenAI's leading GPT-3 are trained on vast volumes of internet data, and learn to write eerily life-like text off human prompts. What they found: While "no currently existing autonomous system could replace the entirety of the IRA," algorithmically based tech paired with experienced human operators produces results that are nothing less than frightening. What to watch: While OpenAI has tightly restricted access to GPT-3, Buchanan notes that it's "likely that open source versions of GPT-3 will eventually emerge, greatly complicating any efforts to lock the technology down."


Beginners Guide To Linear Regression In Python

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Machine Learning is the scientific process of developing an algorithm that learns the pattern from training data and performs inferences on test data.