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DARPA’s AI Algorithms Can Now Control an Actual F-16 in Flight

DARPA, the research arm of the US Department of Defense, recently announced that their AI algorithms can now control a full-scale fighter jet. This accomplishment was demonstrated in early December 2022, over the course of several days, at the Air Force Test Pilot School in California. The AI software was loaded into the X-62A or VISTA, a modified F-16 test aircraft. DARPA’s Air Combat Evolution (ACE) program, which focuses on human-machine collaboration in dogfighting, began in 2019. The AlphaDogfight Trials, a competition between different companies to see who could create the most advanced algorithm for an AI-powered aircraft, took place in 2020.

The ACE program is one of more than 600 Defense Department projects that incorporate artificial intelligence into the nation’s defense programs. In 2018, the government committed to spending up to $2 billion on AI investments over the next five years, with $2.58 billion spent on AI research and development alone in 2022. DARPA hopes to use AI to allow the “human pilot to focus on larger battle management tasks in the cockpit” while the AI controls the jet and provides live-flight data. The ACE program will enable American defense to develop “much smaller autonomous aircraft” while also providing valuable live-flight data. In 2024, four AI-powered L-39s will compete in a live dogfight over Lake Ontario. The Air Force Test Pilot School is investigating how well pilots trust the AI agent and how to calibrate trust between humans and AI.

This technological breakthrough is significant because it demonstrates how artificial intelligence systems can control a fighter jet in flight. It has implications for defense systems, particularly in terms of human-machine collaboration in dogfighting. Pilots can focus on larger battle management tasks by allowing the AI to control the jet. This technology has the potential to become commonplace in defense programs with continued research and development, leading to smaller autonomous aircraft and invaluable live-flight data.

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Superhuman Robotic Boots to Enhance Balance – A Promising Solution for Fall Prevention

Robotic boots have been shown by researchers to improve balance in healthy young adults. The key to improving balance, according to the study, is to have boots that can respond faster than human reaction times. The motorized floors used in the study “pulled the rug out” from under participants, forcing them to stay balanced with their feet in place. The exo-boots were programmed to provide participants with a burst of assistance faster than humanly possible, and the results revealed that only the mode that outperformed the human reaction helped users recover balance faster and prevented them from taking a step toward recovery.

Because falls are the leading cause of health decline in older adults, the development of assistive technology to improve balance can prevent falls and allow people to be active for longer periods of time. The research is a proof-of-concept demonstration that exoskeletons can improve balance in a controlled laboratory setting during a simple upright standing task for young adults who do not have balance issues. The findings show that the nervous system acts to gather information from throughout the body in order to stay upright while standing or walking.

Although much work remains to be done to enable wearable robots to assist with balance in everyday life and improve the lives of people with balance impairments, the results of this study are promising. Wearable robots can be used at other lower-limb joints, such as the knee and hip, to develop artificial intelligence capable of predicting the risk of falling and enabling personalized superhuman balance.

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Digital humans and AI chatbots

In our current AI chat frenzy, we may have overlooked another kind of chatbot that has been quietly emerging: “digital humans.”

These are images on phones, computers and other screens that mimic people. They function in roles like sales assistants, corporate trainers, and social-media influencers, like “Lil Miquela,” an online influencer with nearly 3 million Instagram followers who books herself as a “19-year-old Robot living in LA.“

AI with a human face

Thanks to rapid progress in computer graphics and AI, human faces are now being added to chatbots and other computer-based interfaces for customers, employees, and others.

Alan Dennis, professor of information systems and the John T. Chambers Chair of Internet Systems at the Indiana University Kelley School of Business, has been observing this emerging trend for seven years with colleagues at the University of Sydney and Iowa State University.

In a Feb. 14 Harvard Business Review article, “AI with a Human Face: The case for — and against — digital employees,” Dennis and associates explain how different types of digital humans interact with us in various ways, and when they are most appropriate.

“Digital humans can be a much better choice when it comes to communicating complex instructions or describing features of a product. This is why YouTube instruction videos — rather than pages of text — are so successful,” they note.

Types of digital humans

The researchers identify four types of digital humans:

Virtual agents, whose role is to complete specific, one-time tasks, such as providing instructions to travelers at international airports.

Virtual influencers, who “supply their human followers with experiences” but are not “personalized,” like those employed by the fashion industry.

Virtual assistants, who help users in completing specific tasks, often developing personal relationships with users, which enables them to function as rehabilitation therapists, personal assistants, and coaches, for example.

Virtual companions, who enable older people to stay in their homes longer, which is known to be better for their physical and mental health. They are also much cheaper than assisted living or nursing homes. “Similar opportunities exist in education. Children are more engaged when they watch other children. Thus, a child-aged digital human could, at times, be a more effective teacher than a human adult teacher.”

Reality check

To further explore these ideas, I spoke with professor Dennis. One question: “How real could or should  these images be?”

Dennis said he was concerned about the “uncanny valley” effect and pointed to Soul Machines, an autonomous animation software company that has deployed about 50 digital humans in organizations around the world.

“In a study, about a third of our students found their productions to be in the uncanny valley,” he said. “Some also said they don’t want to talk, they want to type, while others don’t like listening, because people talk so slow … we turn the speed up on videos to 1.5 or 2.”

Smart chatbot faces … and some issues

“Anywhere there’s a chatbot, we could put a digital face on it, and drop it onto your phone, and suddenly, we have an AI agent that looks and sounds like a real human,” Dennis said.

Other possible uses of digital faces he mentioned include customer support and apps like Siri, Alexa and Google Voice. “And we could drop a face into a Zoom chat, where It becomes “another” team member [assuming we can fix ‘Zoom face‘].”

Adding ChatGPT or other language models

“Now imagine combining that with ChatGPT, and it could function as an entry-level employee. People who collaborate with AI will go far. In the future, we’ll be talking about partnering with AI (not just using it), because technology is becoming more and more like a human,” said Dennis.

“Wherever you use a chatbot, we will be able to see a human face, and hopefully, you’ll be able to customize it so you get the look and feel that you want,” said Dennis.

However, “when a digital human can look like any person, there will be avatars to look like famous people, and of course, imposter issues,” he notes.

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Out-of-this-world spacecraft parts: NASA designs with AI

NASA is designing specialized spacecraft parts known as “evolved structures” in as little as an hour or two using commercially available AI software. The evolved structures are intended to be more durable, lighter, and require less assistance from humans. According to Ryan McClelland, the research engineer who pioneered the design of these parts, the evolved structures can save up to two-thirds of the weight and reduce the risk of failure when compared to standard components. Starting with the mission requirements, the AI software draws the surfaces where the part connects to the instrument or spacecraft, and a computer-assisted design specialist draws the surfaces where the part connects to the instrument or spacecraft. The AI software then connects the dots to create complex structure designs.

While AI software can generate complex designs, McClelland admits that algorithms require a human eye because human intuition knows what looks right, and the algorithm can sometimes produce structures that are too thin. The technology is currently being used in a number of NASA missions, including the EXoplanet Climate Infrared TElescope (EXCITE) mission, which is a balloon-borne telescope that studies hot Jupiter-type exoplanets orbiting other stars. AI-assisted design at NASA could allow for the production of larger components in orbit or the construction of structures on the Moon or Mars using materials found there, advancing “In-space Servicing, Assembly, and Manufacturing” (ISAM) capabilities.

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How AI-powered chatbots are revolutionizing the legal industry

Harvey AI, a startup funded by OpenAI, has teamed up with global law firm Allen & Overy to automate legal document drafting and research. Harvey is a generative AI technology that uses OpenAI’s GPT software to save lawyers time and increase efficiency by serving as a starting point for legal work such as contract drafting and review. According to the startup, the deal with Allen & Overy could pave the way for more similar transactions.

Several legal tech firms have recently released AI-powered tools that include the technology for contract drafting and review. Allen & Overy partner David Wakeling believes that law firms that do not adopt generative AI will be at a competitive disadvantage in the long run. By automating repetitive tasks, the technology allows law firms to save time and money, but Wakeling emphasizes that any AI-assisted work will always be reviewed by a human lawyer. Legal work is a good fit for generative AI technology due to the high amount of repetition and text-based learning involved.

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The most in-demand skill is something only humans can do” – Why Management is the Key to the Future of Work

In today’s world, we frequently hear about how technology is replacing jobs, but according to a new LinkedIn report, the most sought-after skills in 2023 will be management, communication, leadership, and teamwork, all of which are uniquely human. The report emphasizes the importance of soft skills such as empathy, motivation, and listening, which are all necessary for leading people and building strong teams.

While there has been criticism leveled at middle managers, many of whom have been tasked with balancing upper-management demands and employee expectations, it is critical to recognize the value of effective managers who have the necessary skills and training. Companies and individuals can invest in people-management training for those who genuinely want to be managers, while also providing alternative ways to reward and advance employees who are good at their jobs but do not want to be managers.

In today’s changing workplace, it is critical to learn how to lead with empathy, as well as how to motivate and listen to our coworkers and employees. We can ensure our relevance in a world where machines are taking over many tasks by developing and honing our soft skills. The ability to connect with others is a uniquely human strength that cannot be replicated by technology, and it is critical for workplace success.

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Protecting businesses from cyber threats with Generative AI

As artificial intelligence (AI) becomes more common, organizations must not only protect themselves from malicious use cases, but also look for ways to defend themselves with AI. Generative AI can detect threats, guide remediation, and help secure cloud and Kubernetes environments. To fully utilize generative AI, businesses must consider new policies, training and output protection, and modernized security auditing. In the future, we must prioritize the protection of AI training and output, the establishment of generative AI usage policies, the modernization of security auditing, data hygiene, the assessment of bias, the creation of new jobs and responsibilities, the use of AI to optimize cyber investments, the enhancement of threat intelligence, and the implementation of a digital trust strategy. While the potential of AI is exciting, it is critical to ensure its ethical use.

As such, businesses must develop strong processes to build resilience against cyber attacks while also regulating its use. Protecting data input and developing prompts for targeted outputs, while also checking outputs for inherent bias, necessitates collaboration between the technology and the people who use it. The proper application of generative AI will provide businesses with the most value while minimizing risks.

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How 10 industries are experimenting with ChatGPT

The rise of artificial intelligence (AI) in the workplace has fueled speculation about how it will affect job security and industry roles. Since November 2022, OpenAI’s ChatGPT, a language model chatbot trained on massive amounts of data, has been in the public domain. While some are concerned about the potential for AI to be abused, others are looking at the potential ways it can improve industries. The following ten industries are experimenting with ChatGPT:

  • Travel: Comparing the AI’s travel recommendations to those of an experienced advisor.
  • Legal: Using artificial intelligence to answer legal questions about a case and incorporating ChatGPT’s responses into a decision.
  • Real Estate: Using ChatGPT to generate property summaries for listings by typing keywords.
  • Marketing: Writing video scripts for promotional videos with ChatGPT.
  • Education: Students demonstrate mastery of a topic by teaching ChatGPT. Creating lesson plans and materials with ChatGPT.
  • Law Making: AI writing bills have been introduced in Massachusetts to regulate generative artificial intelligence.
  • Health: Testing the ability of ChatGPT to diagnose patients.
  • Publishing: Putting the AI’s ability to write articles to the test.
  • Tech: Without prior experience, write good code quickly, debug code, and create effective malware.
  • Government: Using ChatGPT to produce more human-like responses for citizens.

The rise of AI provides industries with a unique opportunity to improve their operations, but it must be used with caution … we are only in the first iterations of applying these technologies and mistakes will occur.

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The Future of Music is in AI: David Guetta’s Insights

Super-producer and DJ David Guetta recently made an intriguing statement about the future of music, claiming that it lies in AI technology. While he recognizes that AI is a tool that cannot replace an artist’s taste and emotion, he believes it has the potential to define new musical styles.

Guetta compares the evolution of AI to the invention of influential musical instruments such as the TR-909 and sampler, noting that each new music style is the result of a new technology. This finding is significant because it implies that artificial intelligence can be used to push the boundaries of music and create new genres.

This statement is especially significant for marketers and copywriters because it indicates that the future of music and creativity is inextricably linked to technology. As a result, brands and businesses must keep up with emerging technological trends and incorporate them into marketing campaigns and copywriting. This not only keeps them relevant, but also ensures that their messaging and content resonate with and capture the attention of their audiences.

David Guetta’s comments about the future of music suggest that AI will be critical in defining new musical styles. This insight emphasizes the importance of incorporating emerging technological trends in marketing and copywriting in order to remain relevant and capture audiences’ attention.

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Generative AI Models Struggle to be Adopted by Businesses: Four Major Obstacles

Though business leaders have been intrigued by the public reaction and engagement to this emerging technology, it still requires the right talent, governance, maturity, and budget to succeed. The top four gaps and barriers to entry that businesses encounter when implementing generative AI models are IT governance, data gathering and quality, maturity of tech stack, and cost. This article further explains that governance models should include guiding principles, focused on privacy, data security, algorithmic transparency within AI models, and cybersecurity vulnerabilities. Data quality is the second most significant capability gap, while generative AI adoption requires a level of modernization that most non-traditional tech companies are still embracing. Cost, although not considered a capability gap, is a barrier to entry for most businesses as large models require a lot of computing power. Vendors have already started customizing generative AI models to specific business needs, making it more accessible and affordable for enterprises.

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