Digital transformation is well underway at most companies these days. As more processes become digitized, more companies recognize the opportunities for Artificial Intelligence-driven efficiency gains. However, greater AI adoption still faces stumbling blocks, often present in the nature of an organization’s workflow.
One of the major stumbling blocks to AI adoption among organizations is the lack of a data-driven culture. Here are three ways organizations can become more data-driven to leverage AI better.
Universal media synthesis, the innovation pyramid and autolism — part 1
AI can now generate images and text that’s as good as a human. What happens when AI can generate all kinds of media as good as a human?
******Remember, the future is unknowable. I do not know the future. I speculate on what m_i_g_h_t happen given a set of starting assumptions. I can speculate about what’s possible but make sure to separate speculation from fact. If you understand these pretenses, then let us speculate about the future of technology.
Special Thanks to the following individuals for creating such great background music:
Ray Kurzweil is one of the world’s leading inventors, thinkers, and futurists, with a thirty-year track record of accurate predictions. Called “the restless genius” by The Wall Street Journal and “the ultimate thinking machine” by Forbesmagazine, he was selected as one of the top entrepreneurs by Inc. magazine, which described him as the “rightful heir to Thomas Edison.” PBS selected him as one of the “sixteen revolutionaries who made America.” Ray was the principal inventor of the first CCD flat-bed scanner, the first omni-font optical character recognition, the first print-to-speech reading machine for the blind, the first text-to-speech synthesizer, the first music synthesizer capable of recreating the grand piano and other orchestral instruments, and the first commercially marketed large-vocabulary speech recognition software. Ray received a Grammy Award for outstanding achievements in music technology; he is the recipient of the National Medal of Technology, was inducted into the National Inventors Hall of Fame, holds twenty-one honorary Doctorates, and honors from three U.S. presidents. Ray has written five national best-selling books, including New York Times best sellers The Singularity Is Near (2005) and How To Create A Mind (2012). He is Co-Founder of Singularity Group and a Principal Researcher and AI Visionary at Google, looking at the long-term implications of technology and society.
The Computational Health Informatics Program (CHIP)
CHIP, founded in 1994, is a multidisciplinary applied research and education program at Boston Children’s Hospital. For more information, please visit our website www.chip.org.
Signaling its interest in text-generating AI systems like ChatGPT, Quora this week launched a platform called Poe that lets people ask questions, get instant answers and have a back-and-forth dialogue with AI chatbots.
Short for “Platform for Open Exploration,” Poe — which is invite-only and currently only available on iOS — is “designed to be a place where people can easily interact with a number of different AI agents,” a Quora spokesperson told TechCrunch via text message.
“We have learned a lot about building consumer internet products over the last 12 years building and operating Quora. And we are specifically experienced in serving people who are looking for knowledge,” the spokesperson said. “We believe much of what we’ve learned can be applied to this new domain where people are interfacing with large language models.”
Robots like Digit are purpose-built to do tasks in environments made for humans. We aren’t trying to just mimic the look of people or make a humanoid robot.
Every design and engineering decision is looked at through a function-first lens. To easily walk into warehouses and work alongside people, to do the kinds of dynamic reaching, carrying, and walking that we do, Digit has some similar characteristics.
Our Co-Founder and Chief Technology Officer Jonathan Hurst, discusses the difference between humanoid and human-centric robotics.
At Agility, we make robots that are made for work. Our robot Digit works alongside us in spaces designed for people. Digit handles the boring and repetitive tasks that are meant for a machine, which allows companies and their people to focus on the work that requires the human element.
Trey Parker and Matt Stone’s AI studio Deep Voodoo said Wednesday that it has secured a $20 million in an investment round led by Connect Ventures. The South Park creators’ startup said it will use the capital to accelerate its development of deep-fake technology, VFX services and original synthetic media projects.
Connect Ventures is an investment partnership between CAA and venture capital firm New Enterprise Associates and represents the first outside capital raise for Deep Voodoo, which was previously funded by Parker and Stone’s entertainment company Park County.
Parker and Stone originally began building out their deep fake technology in early 2020, assembling a team of artists for a feature film they had developed. When the film was suspended amid the Covid shutdown, they pivoted to building out those deep-fake tools.
For some, automation will usher in a labor-free utopia; for others, it signals a disastrous age-to-come. Yet whether seen as dream or nightmare, automation, argues Munn, is ultimately a fable that rests on a set of triple fictions. There is the myth of full autonomy, claiming that machines will take over production and supplant humans. But far from being self-acting, technical solutions are piecemeal; their support and maintenance reveals the immense human labor behind autonomous processes. There is the myth of universal automation, with technologies framed as a desituated force sweeping the globe. But this fiction ignores the social, cultural, and geographical forces that shape technologies at a local level. And, there is the myth of automating everyone, the generic figure of the human at the heart of automation claims. But labor is socially stratified and so automation’s fallout will be highly uneven, falling heavier on some (immigrants, people of color, women) than others. Munn moves from machine minders in China to warehouse pickers in the United States to explore the ways that new technologies do (and don’t) reconfigure labor. Combining this rich array of human stories with insights from media and cultural studies, Munn points to a more nuanced, localized, and racialized understanding of the future of work.
Technology has given us everything from smart TVs that can hear you talking to self-driving cars, but before we became the digitally-driven society we are today, fear of new technology commonly served as one of the greatest threats to innovation. What we see as dated and relatively harmless inventions of the past were once the new technology that people freaked out about. Without an efficient way to educate the masses about the latest, hottest new inventions of their era, paranoia and confusion quickly took the place of logic and curiosity for many consumers. While many of these inventions are now seen as revolutionary and their modern counterparts are a part of our daily lives, there was once a time when these gadgets were some of the most frightening topics of discussion.
