Because we live in a dystopian healthcare hell, AI chip manufacturer Nvidia has announced a partnership with an AI venture called Hippocratic AI to replace nurses with freaky AI “agents.”
These phony nursing robots cost hospitals and other health providers $9 an hour, a fee that barely falls above the US minimum hourly wage, and far below the average hourly wage for registered nurses (RNs.)
In a press release, Hippocratic AI described the disturbingly cheap nurses as part of an effort to mitigate staffing issues. The company also claims that the agents won’t be doing any diagnostic work, and will instead be doing “low-risk,” “patient-facing” tasks that can take place via video call.
This video explores the future of Mars colonization and terraforming from 2030 to 3000. Watch this next video about the 10 stages of AI: • The 10 Stages of Artificial Intelligence. 🎁 5 Free ChatGPT Prompts To Become a Superhuman: https://bit.ly/3Oka9FM 🤖 AI for Business Leaders (Udacity Program): https://bit.ly/3Qjxkmu. ☕ My Patreon: / futurebusinesstech. ➡️ Official Discord Server: / discord.
💡 On this channel, I explain the following concepts: • Future and emerging technologies. • Future and emerging trends related to technology. • The connection between Science Fiction concepts and reality.
Whether it’s a powered prosthesis to assist a person who has lost a limb or an independent robot navigating the outside world, we are asking machines to perform increasingly complex, dynamic tasks. But the standard electric motor was designed for steady, ongoing activities like running a compressor or spinning a conveyor belt – even updated designs waste a lot of energy when making more complicated movements.
Researchers at Stanford University have invented a way to augment electric motors to make them much more efficient at performing dynamic movements through a new type of actuator, a device that uses energy to make things move. Their actuator, published March 20 in Science Robotics, uses springs and clutches to accomplish a variety of tasks with a fraction of the energy usage of a typical electric motor.
“Rather than wasting lots of electricity to just sit there humming away and generating heat, our actuator uses these clutches to achieve the very high levels of efficiency that we see from electric motors in continuous processes, without giving up on controllability and other features that make electric motors attractive,” said Steve Collins, associate professor of mechanical engineering and senior author of the paper.
Today we’re introducing SceneScript, a novel method for reconstructing environments and representing the layout of physical spaces from @RealityLabs Research.
The term “artificial general intelligence” (AGI) has become ubiquitous in current discourse around AI. OpenAI states that its mission is “to ensure that artificial general intelligence benefits all of humanity.” DeepMind’s company vision statement notes that “artificial general intelligence…has the potential to drive one of the greatest transformations in history.” AGI is mentioned prominently in the UK government’s National AI Strategy and in US government AI documents. Microsoft researchers recently claimed evidence of “sparks of AGI” in the large language model GPT-4, and current and former Google executives proclaimed that “AGI is already here.” The question of whether GPT-4 is an “AGI algorithm” is at the center of a lawsuit filed by Elon Musk against OpenAI.
Given the pervasiveness of AGI talk in business, government, and the media, one could not be blamed for assuming that the meaning of the term is established and agreed upon. However, the opposite is true: What AGI means, or whether it means anything coherent at all, is hotly debated in the AI community. And the meaning and likely consequences of AGI have become more than just an academic dispute over an arcane term. The world’s biggest tech companies and entire governments are making important decisions on the basis of what they think AGI will entail. But a deep dive into speculations about AGI reveals that many AI practitioners have starkly different views on the nature of intelligence than do those who study human and animal cognition—differences that matter for understanding the present and predicting the likely future of machine intelligence.
The original goal of the AI field was to create machines with general intelligence comparable to that of humans. Early AI pioneers were optimistic: In 1965, Herbert Simon predicted in his book The Shape of Automation for Men and Management that “machines will be capable, within twenty years, of doing any work that a man can do,” and, in a 1970 issue of Life magazine, Marvin Minsky is quoted as declaring that, “In from three to eight years we will have a machine with the general intelligence of an average human being. I mean a machine that will be able to read Shakespeare, grease a car, play office politics, tell a joke, have a fight.”
The UN General Assembly on Thursday adopted a landmark resolution on the promotion of “safe, secure and trustworthy” artificial intelligence (AI) systems that will also benefit sustainable development for all.
Leading computer scientists from around the world have shared their vision for the future of artificial intelligence—and it resembles the capabilities of Star Trek character “The Borg.”
But the reality is that the hard work starts now. The law will enter into force in May, and people living in the EU will start seeing changes by the end of the year. Regulators will need to get set up in order to enforce the law properly, and companies will have between up to three years to comply with the law.
UK-based construction technology firm Automated Architecture (AUAR) has bagged $3.2 million in funding to advance its mission to automate the construction process to solve housing-related issues.
AUAR is creating a network of dispersed micro-factories for environmentally friendly timber homes. AUAR claims that it presents an alternative vision for the built environment, in which local ecosystems comprising developers, contractors, architects, and communities are empowered to construct better homes instead of centralized automation in massive factories.
