Toyota has started constructing a 175-acre smart city in Japan that will work on artificial intelligence and futuristic technologies and serve as a “living laboratory”, the company has announced.
Construction
began this week on the project dubbed “Woven City”, at a site at the
base of Japan’s Mount Fuji, about 62 miles from Tokyo.
The city is
being designed as a testing ground for technologies that could be
rolled out across urban environments, including robotics, interconnected
smart homes and artificial intelligence.
The company’s president
Akio Toyoda broke ground at the site on Tuesday in a ceremony involving
local officials of Shizuoka Prefecture, where the new city is located.
Toyota,
which first announced the project at CES 2020 in January last year,
says the city will have three types of roads which are all linked to
each other at the ground level – one thoroughfare for pedestrians, one
for pedestrians using personal mobility vehicles like e-scooters, and
one dedicated solely to self-driving vehicles. The company said there
would be one conventional road running underneath the city to provide
goods transportation.
Toyota launched its own self-driving
vehicle, the e-Palette, in 2018, and it is expected that they will make
up the bulk of the Woven City project’s transport infrastructure. The
company has previously described them as “scalable and customisable” for
a range of functions include ride-sharing, delivery services and even
mobile offices and hotels.
Why do you believe what you believe? Some people have a really solid
answer to that question, but much of the population never thinks much
about deeper questions such as this. In fact, for most Americans it is
simply easier to let others do their thinking for them. Today, most of
us spend multiple hours each day absorbing information through a screen,
and most of the content that is fed to us through our televisions,
phones, tablets and computers is controlled by the elite. And if you
allow anyone to feed information into your mind for several hours every
day, it is going to have a dramatic impact on how you view the world.
When I was younger, one of my favorite movies was “The Matrix”, and I
think that it is a really good metaphor for what is going on in our
society today. In the film, nearly the entire human population was
plugged into a system which continuously fed a computer-generated
reality into their minds that wasn’t real at all. Later on, I
eventually came to realize that we are willingly doing the same thing to
ourselves. Our personal interactions with one another are extremely
limited, but we willingly “plug in” to the enormous matrix of news,
information and entertainment that the elite have constructed for many
hours each day.
According to numbers that were released earlier this year, the average American spends more than three hours watching television and more than three hours on mobile devices every single day…
If Americans from previous generations could visit our society right
now, they would probably be horrified that we are all constantly staring
at our screens like some sort of zombies.
And perhaps it wouldn’t be so bad if we were feeding our minds
healthy things, but instead most of what we are absorbing is garbage
that has been produced by the elite. More..
The
backlash against the high tech mob is so obvious
that no sane person can deny that their version of acceptable
thinking requires banning Free Speech. The genie is out of the
lamp and the only way to prevent these demons from repeating
their censorship is to cork the bottle of any product offered
by these companies. Utopia for the authoritarian collectivists
necessitates that they conjure up twisted and absurd content
targets as hate speech in a desperate attempt to rationalize
the purging of counter opinions to their orthodox "PC"
Communist Manifesto. In essence, the "so called" left has
become the model of fascism by and under Silicon Valley's
techno plutocrats. Merging Fabian ideals with state/corporatist
absolutism produces a deformed corporeality by algorithms
in an artificial intelligence society.
Algorithms
function as filters to identify dangerous voices of reason and
common sense. Eradicating any kind of dissent or historic cultural
viewpoints is automated in the digital cloud of approved
thinking. The canard that the masters of artificial truth are private
companies and are not subject to Bill of Right protections is
an insult to anyone who is committed to the building of a free
society. Google, YouTube, Twitter, Facebook and Instagram have
emerged as monopolies that restrict speech and excel at censorship.
Hundreds of Google employees are up in arms over the company's
partnership with the Pentagon in AI technology, fearing it may be used
for war. Experts told RT the "questionable" alliance could result in
"disaster for humanity."
Google employees wrote a
letter to the company's CEO, Sundar Pichai, calling on the US tech giant
to immediately pull out of a controversial program that many fear could
be used for warfare.
"We believe that Google should not be in the business of war," the letter obtained by The New York Times and published earlier this week stated.
Gizmodo
broke the news about Google's partnership with the US Department of
Defense (DoD) last month, adding that Project Maven, whose stated mission is to "accelerateDoD's integration of big data and machine learning,"
was established in April 2017. The project will see Google developing
AI surveillance to help the US military scrutinize video footage
captured by US government drones "to detect vehicles and other objects, track their motions, and provide results to the Department of Defense."
Google claims that the technology is human-friendly and is actually designed to "save lives" and "scoped to be for non-offensive purposes." But Noel Sharkey, Emeritus professor of AI at Sheffield University, told RT that the fears of Google employees "are correct."
Back in May, Google revealed its AutoML project; artificial intelligence (AI) designed to help them create
other AIs. Now, Google has announced that AutoML has beaten the human
AI engineers at their own game by building machine-learning software
that’s more efficient and powerful than the best human-designed systems.
An AutoML system recently broke a record for categorizing images by
their content, scoring 82 percent. While that’s a relatively simple
task, AutoML also beat the human-built system at a more complex task
integral to autonomous robots and augmented reality: marking the
location of multiple objects in an image. For that task, AutoML scored
43 percent versus the human-built system’s 39 percent.
These results are meaningful because even at Google, few people have
the requisite expertise to build next generation AI systems. It takes a
rarified skill set to automate this area, but once it is achieved, it
will change the industry. “Today these are handcrafted by machine
learning scientists and literally only a few thousands of scientists
around the world can do this,” WIRED reports Google CEO Sundar Pichai said. “We want to enable hundreds of thousands of developers to be able to do it.”
Much of metalearning is about imitating human neural networks and trying
to feed more and more data through those networks. This isn’t — to use
an old saw — rocket science. Rather, it’s a lot of plug and chug work
that machines are actually well-suited to do once they’ve been trained.
The hard part is imitating the brain structure in the first place, and
at scales appropriate to take on more complex problems.
The rapid development of so-called NBIC technologies –
nanotechnology, biotechnology, information technology and cognitive
science – are giving rise to possibilities that have long been the
domain of science fiction. Disease, ageing and even death are all human
realities that these technologies seek to end.
They may enable us to enjoy greater “morphological freedom” – we
could take on new forms through prosthetics or genetic engineering. Or
advance our cognitive capacities. We could use brain-computer interfaces to link us to advanced artificial intelligence (AI).
Nanobots
could roam our bloodstream to monitor our health and enhance our
emotional propensities for joy, love or other emotions. Advances in one
area often raise new possibilities in others, and this “convergence” may
bring about radical changes to our world in the near-future.
“Transhumanism” is the idea that humans should transcend their
current natural state and limitations through the use of technology –
that we should embrace self-directed human evolution. If the history of
technological progress can be seen as humankind’s attempt to tame nature
to better serve its needs, transhumanism is the logical continuation:
the revision of humankind’s nature to better serve its fantasies. More
Modern sensors can see farther than humans. Electronic circuits can
shoot faster than nerves and muscles can pull a trigger. Humans still
outperform armed robots in knowing what to shoot at — but new research
funded in part by the Army may soon narrow that gap.
Researchers from DCS Corp and the Army Research Lab fed datasets of
human brain waves into a neural network — a type of artificial
intelligence — which learned to recognize when a human is making a
targeting decision. They presented their paper on it at the annual Intelligent User Interface conference in Cyprus in March.
Why is this a big deal? Machine learning relies on highly structured
data, numbers in rows that software can read. But identifying a target
in the chaotic real world is incredibly difficult for computers. The
human brain does it easily, structuring data in the form of memories,
but not in a language machines can understand. It’s a problem that the
military has been grappling with for years.
“We often talk about deep learning. The challenge there for the
military is that that involves huge datasets and a well-defined
problem,” Thomas Russell, the chief scientist for the Army, said at a
recent National Defense Industrial Association event. “Like Google just solved the Go game problem.”
Last year, Google’s DeepMind lab showed
that an AI could beat the world’s top player in the game of Go, a game
considered exponentially harder than chess. “You can train the system to
do deep learning in a [highly structured] environment but if the Go
game board changed dynamically over time, the AI would never be able to
solve that problem. You have to figure out...in that dynamic environment
we have in the military world, how do we retrain this learning process
from a systems perspective? Right now, I don’t think there’s any way to
do that without having the humans train those systems.”
SAN FRANCISCO – Forget the Terminator. The next robot on the horizon may be wearing a lab coat.
Artificial intelligence (AI)
is already helping scientists form testable hypotheses that enable
experts to run real experiments, and the technology may soon be poised
to help businesses make decisions, one scientist says.
However, that doesn't mean the machines will be taking over from
humans entirely. Instead, humans and machines have complementary
skillsets, so AI could help researchers with the work they already do,
Laura Haas, a computer scientist and director of the IBM Research
Accelerated Discovery Lab in San Jose, California, said here Wednesday
(Dec. 7) at the Future Technologies Conference.
"The machine will come to be a strong partner to humans," akin to the android Data on the TV series "Star Trek: The Next Generation," Haas said.
Big Data
Though many people fear a future where our robot overlords surpass
humans in almost every capacity, in reality, machines have long outpaced
mere mortals at many tasks, such as doing incredibly fast mathematical
computations. But this dominance is nowhere clearer than in the realm of
Big Data.
"Global scientific output doubles every nine years; 90 percent of the
data in the world today has been created in the last two years alone;
2.5 exabytes of data are created every day," Haas said. (An exabyte is
equivalent to 1 billion gigabytes.)
In the competition between man and machine, computers are the
undisputed winners at processing and assimilating all this information,
Haas said.
Angel of death
After IBM's Watson trounced Ken Jennings in "Jeopardy!",
Dr. Olivier Lichtarge, a molecular biologist at Baylor College of
Medicine in Texas, contacted Haas' group to see if similar technology
could help him in his research.
Lichtarge was looking at a specific gene, called p53, which is dubbed
the cell's "angel of death," Haas said. The gene helps direct the cell
through its life cycle and kills aging or damaged cells. In about 50
percent of cancer cases, there is some problem with how p53 is
functioning, Haas added. What's more, research had revealed that certain
molecules, called kinases, played a key role in the functioning of p53.
But, there were more than 70,000 scientific papers written about this
gene, and 5,000 new studies are cropping up each year. A lab assistant
could never read all the literature to identify good kinase candidates,
so Lichtarge asked the group to build a program that could read through
the existing literature and then identify molecules that might act as
kinases to p53.
The AI assistant scanned through hordes of medical abstracts from
studies published before 2004, and identified nine different kinase
molecules that were potentially affecting the activity of p53.
In the ensuing decade, other researchers had identified seven of those
molecules as kinases. Two, however, were never mentioned in all of the
literature.
"They went off and tried to do some experimentation in the lab," Haas
said. "About a year later, we had proof both in vivo and in vitro
experimentation that these two were kinases."
Of course, Watson isn't yet up to the level of a brilliant and trained
research scientist. In this instance, AI was used to tackle a narrow,
straightforward problem that was very well posed, and it also benefited
from a wealth of scientific data, Haas said.
But the results were exciting nonetheless, she said. Live Science
