Moving towards Artificial General Intelligence?
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Summary: A new artificial intelligence model automatically learns higher-level language patterns that can apply to different languages, enabling it to achieve better results.
Source: McGill University.
Human languages are notoriously complex, and linguists have long thought it would be impossible to teach a machine how to analyze speech sounds and word structures in the way humans do.
Humanoid artificial intelligence is coming and there’s a good chance it may come to life in Vancouver.
That’s because some of the brains at work creating AI – human-like AI – live and work here. The odds that they will succeed are high, they have an amazing track record. One of those brains is the mastermind behind the development of quantum computing that has manifested itself into the company known as D-Wave.
Continue reading “Can AI change the meaning of being human? (w/ Geordie Rose, Sanctuary AI)” »
Live biological neurons show more about how a brain works than AI ever will.
Scientists have shown for the first time that 800,000 brain cells living in a dish can perform goal-directed tasks. In this case, they played the simple tennis-like computer game, Pong. The results of the Melbourne-led study are published today (October 12) in the journal Neuron.
Now the researchers are going to investigate what happens when their DishBrain is affected by medicines and alcohol.
An artificial intelligence created by the firm DeepMind has discovered a new way to multiply numbers, the first such advance in over 50 years. The find could boost some computation speeds by up to 20 per cent, as a range of software relies on carrying out the task at great scale.
Matrix multiplication – where two grids of numbers are multiplied together – is a fundamental computing task used in virtually all software to some extent, but particularly so in graphics, AI and scientific simulations. Even a small improvement in the efficiency of these algorithms could bring large performance gains, or significant energy savings.
The biggest number in the world Agnijo Banerjee at New Scientist Live this October.
Chatbots are starting to muse about life, death and religion. But could these silicon philosophers one day gain consciousness? Or are they just getting good at mimicking it?
UW Medicine researchers have found that algorithms are as good as trained human evaluators at identifying red-flag language in text messages from people with serious mental illness. This opens a promising area of study that could help with psychiatry training and scarcity of care.
The findings were published in late September in the journal Psychiatric Services.
Text messages are increasingly part of mental health care and evaluation, but these remote psychiatric interventions can lack the emotional reference points that therapists use to navigate in-person conversations with patients.
In an effort to streamline the process of diagnosing patients with multiple sclerosis and Parkinson’s disease, researchers used digital cameras to capture changes in gait—a symptom of these diseases—and developed a machine-learning algorithm that can differentiate those with MS and PD from people without those neurological conditions.
Their findings are reported in the IEEE Journal of Biomedical and Health Informatics.
The goal of the research was to make the process of diagnosing these diseases more accessible, said Manuel Hernandez, a University of Illinois Urbana-Champaign professor of kinesiology and community health who led the work with graduate student Rachneet Kaur and industrial and enterprise systems engineering and mathematics professor Richard Sowers.
QNTYM Railway is a ‘software level’ application that can be deployed on current hardware meaning there will be no need for changes in physical network infrastructure (hardware). The QNTYM Railway is an inherently quantum secure, self-defending, resilient, digital infrastructure capable of lightning-fast speed with a significant sustainability proposition. From a command & control standpoint, the QNTYM Railway is also integrated with leading vendors where users can benefit from having threat intel, vulnerability, device & incident response management capabilities all automated and in one place, hence reducing complexity.
In terms of speed, the QNTYM Railway has demonstrated consistent throughput speeds of 350+ Mbit/s, (and above). The QNTYM Railway provides integration and interoperability that is in a class of its own allowing technology to reach new levels. For the past year, QDEx Labs has been stress-assessing the QNTYM Railway across three interconnected cloud environments (AWS, Google Cloud, and Azure); they found that not only are they consistently experiencing the minimum requirement of 250 Mbit/s for 8k video streaming, but they are also, in fact, recording data streams reaching 3 to 4 times that amount with little to no processor load and added latencies in the microsecond (NOT millisecond) range.
The bottom line is that this architecture has now proven capable of hosting an ultra-realistic 3D metaverse. Results like these are something that Web3 and Metaverse projects currently lack and will require.
It’s unclear what “Blood-Wing” in the top-right corner refers to, but the drone itself is called Red Wing. According to the description, this small aerial vehicle could travel to a weak point behind the enemy lines and perform a “surprise attack” by deploying the robot dog. In one envisioned scenario, this four-legged machine “can be placed on the roof of the enemy to occupy the commanding heights to suppress firepower.”
Mounted on its back is what appears to be a Chinese QBB-97 (designated as Type 95 LGM in the United States). This 5.8 mm light support weapon can fire up to 650 rounds a minute.
No further specifications have been made available, but the drone and robodog pairing seems designed primarily for use in urban environments that are notoriously difficult for human foot soldiers to infiltrate. It could, for example, be used to scout ahead, take out hard-to-access targets or create a diversion. Kestrel Defence explains that ground troops, supported from above, could conduct “a three-dimensional pincer attack on the enemy in the building.”
