Hypergiant, a startup launched last year to address the execution gap in bringing applied AI and machine learning technologies to bear for large companies, has signed on a high-profile new advisor to help out with the new'Galactic Systems' division of its services lineup. Hypergiant founder CEO Ben Lamm also serves as an Advisory Council Member for The Planetary Society, the nonprofit dedicated to space science and exploration advocacy that's led by Nye who acts as the Society's CEO. Nye did some voiceover work for the video at the bottom of this post for Hypergiant through the connection, and then decided to come on in a more formal capacity as an official advisor working with the company. Nye was specifically interested in helping Hypergiant to work on AI tech that touch on a couple of areas he's most passionate about. "Hypergiant has an ambitious mission to address some big problems using artificial intelligence systems," Nye explained via email.

The fight against videos altered by the use of artificial intelligence just got a new ally. According to researchers at UC Berkeley and the University of Southern California, a new algorithm can help spot whether a video has been manipulated via a process known as'deepfaking.' Counter-intuitively, the tool that scientists say will aid them in their crusade against faked videos happens to be the very same tool that helps make the videos in the first place: artificial intelligence. The fight against videos altered by the use of artificial intelligence just got a new ally. Pictured is a grab from a deep fake video where Steve Buscemi's face is superimposed over Jennifer Lawrence's body Deepfakes are so named because they utilize deep learning, a form of artificial intelligence, to create fake videos.

When we began our 14-week tech health sprint in October 2018, we did not realize the profound lessons we would learn in just a few months. Together with federal agencies and private sector organizations, we demonstrated the power of applying artificial intelligence (AI) to open federal data. Through this collaborative process, we showed that federal data can be turned into products for real-world health applications with the potential to help millions of Americans have a better life. Joshua Di Frances, the executive director of the Presidential Innovation Fellows (PIF) program, says that this collaboration across agencies and private companies represents a new way of approaching AI and federal open data. "Through incentivizing links between government and industry via a bidirectional AI ecosystem, we can help promote usable, actionable data that benefits the American people," Di Frances said.

Ex-prime minister David Cameron has taken a job at Affiniti, one of the world's largest artificial intelligence companies, which specialises in the use of AI in sales. As chair of the company's advisory board, Mr Cameron says he will be helping support its work to transform the future of customer service and interpersonal communications. While Mr Cameron may not have predicted the UK's future in Europe, there's no doubt that backing the use of AI in sales is a better bet. "AI and machine-learning are the next evolution of the digital revolution," says Brendan Dykes, director of product marketing at customer experience and call centre technology vendor Genesys. "Like the incoming tide, you can ignore it, but it will continue to come and you can either ride the wave or be swept away by it."

For now, the NSA is exploring the use of artificial intelligence to detect vulnerabilities. "We are experimenting and developing'self-healing networks,' where we see a vulnerability and the vulnerability is recognized rapidly and patched or mitigated," NSA Director Gen. Paul Nakasone explained in his Joint Forces Quarterly interview. Machine learning eventually could help ease the immense workload placed on each cyber staffer at the agency, Neal Ziring, NSA's Technical Director for Capabilities told CyberScoop. "We're going to need, at the very least, ML techniques to pull signal out of the noise so that the defenders, the operators can be informed [and] spend their time on the most critical events or anomalies rather than trying to make sense of this huge data space manually," Ziring said.

WASHINGTON - U.S. consumers will delay or forgo technology upgrades if President Donald Trump imposes a new round of 25 percent tariffs on Chinese goods, slowing the U.S. innovation engine, technology industry executives said on Monday. Trump's administration is preparing to levy tariffs on an additional $300 billion worth of Chinese imports after a public comment period ends on July 2 if the U.S. and Chinese presidents cannot relaunch talks to end their trade war. The two countries have been at odds since July 2018 over a host of U.S. demands that Beijing adopt policy changes that would better protect American intellectual property and make China's market more accessible to U.S. companies. Consumer technology products, including cellphones, laptop and tablet computers, smart speakers and video gaming consoles, would make up $167 billion of that $300 billion total, or more than half the target list, said Sage Chandler, vice president of international trade for the Consumer Technology Association. Chandler told a hearing on the tariffs hosted by the U.S. Trade Representative's office that imposing the tariffs would raise the retail price of cellphones by an average of $70, while the price of laptop computers would rise by $120 and video game consoles by $56.

The scholars focused on combating the malicious use of AI by terrorists. Their findings were published in the journal Russia in Global Affairs. Much has been written on the threats that artificial intelligence (AI) can pose to humanity. Today, this topic is among the most discussed issues in scientific and technical development. Despite the fact that so-called Strong AI, characterised by independent systems thinking and possibly self-awareness and will power, is still far from reality, various upgraded versions of Narrow AI are now completing specific tasks that seemed impossible just a decade ago.

This documentary projects the effects and dangers of Artificial Intelligence (AI) developments for next generations. The video addresses lots of examples in both negative and positive dimensions for using and developing Artificial Intelligence. In my opinion, one of the most important messages of this movie is that speakers in the movie believe that the development of AI is beneficial but it could misuse in lots of malicious areas. Example of that might be within war machines or development of mass destruction weapons which could seriously jeopardize our lives. The message of this movie is clearly states that machines can easily reproduce and duplicate themselves therefore development of full AI could spell the end of the human race.

Intelligent agents can cope with sensory-rich environments by learning task-agnostic state abstractions. In this paper, we propose mechanisms to approximate causal states, which optimally compress the joint history of actions and observations in partially-observable Markov decision processes. Our proposed algorithm extracts causal state representations from RNNs that are trained to predict subsequent observations given the history. We demonstrate that these learned task-agnostic state abstractions can be used to efficiently learn policies for reinforcement learning problems with rich observation spaces. We evaluate agents using multiple partially observable navigation tasks with both discrete (GridWorld) and continuous (VizDoom, ALE) observation processes that cannot be solved by traditional memory-limited methods. Our experiments demonstrate systematic improvement of the DQN and tabular models using approximate causal state representations with respect to recurrent-DQN baselines trained with raw inputs.

This article describes the application of soft computing methods for solving the problem of locating garbage accumulation points in urban scenarios. This is a relevant problem in modern smart cities, in order to reduce negative environmental and social impacts in the waste management process, and also to optimize the available budget from the city administration to install waste bins. A specific problem model is presented, which accounts for reducing the investment costs, enhance the number of citizens served by the installed bins, and the accessibility to the system. A family of single- and multi-objective heuristics based on the PageRank method and two mutiobjective evolutionary algorithms are proposed. Experimental evaluation performed on real scenarios on the cities of Montevideo (Uruguay) and Bahia Blanca (Argentina) demonstrates the effectiveness of the proposed approaches. The methods allow computing plannings with different trade-off between the problem objectives. The computed results improve over the current planning in Montevideo and provide a reasonable budget cost and quality of service for Bahia Blanca.