Interesting*, and well done to the team for making it clear it's an Algorithm not jumping on the so-called AI bandwagon.
*As a 50-something male I'm in the danger zone, although the last PSA test was, thankfully, negative.
An algorithm capable of estimating the risk that a particular patient will develop prostate cancer over the next five years should be used in a national screening program in the UK, one of the software's creators has said. One in eight men in the United Kingdom will be diagnosed with prostate cancer in their lifetime, …
In another area of medicine, it is becoming recognised that some people require a different medicine regime. The science has indicated that this can be due to a specific genetic factor (a particular SNP on a gene).
The positive is that people with this SNP are seeing better chances of getting the different medicine. Some consultants accept that it is justified despite its higher cost.
Most of the patients have had a private gene test - it has not advanced to the point of being widely available on the NHS.
The negative is that those who do not have that SNP are less likely to get it. Despite genetic research, being a fairly young field, is still discovering new SNPs which have the same indication for the other treatment.
The statistics are clear across the population. But population statistics do not apply to the individual. That patient either does, or does not, need the other treatment. The SNP should be seen more as an automatic route, and an explanation. But others should not be excluded from being assessed on a clinical basis, maybe given a trial of the other medicine to see if it helps.
Usually fortunately the cancer is benign, most people diagnosed will die of something else, so diagnosis can cause unnecessary worry and unnecessary interventions can have devastating side effects.
The need is for a test to identify whether the cancer is benign or malignant. Preferably without an autopsy which can cause damage.
Some tests are being developed. A small test reported last month where people who had been diagnosed with the cancer were injected with a sugary solution that contained a marker that can be detected by an MRI scan (cancer loves sugar). This was effective at distinguishing malignant cancers that need intervention and benign cancers that simply need monitoring.
IBM chairman and CEO Arvind Krishna says it offloaded Watson Health this year because it doesn't have the requisite vertical expertise in the healthcare sector.
Talking at stock market analyst Bernstein's 38th Annual Strategic Decisions Conference, the big boss was asked to outline the context for selling the healthcare data and analytics assets of the business to private equity provider Francisco Partners for $1 billion in January.
"Watson Health's divestment has got nothing to do with our commitment to AI and tor the Watson Brand," he told the audience. The "Watson brand will be our carrier for AI."
Qualcomm knows that if it wants developers to build and optimize AI applications across its portfolio of silicon, the Snapdragon giant needs to make the experience simpler and, ideally, better than what its rivals have been cooking up in the software stack department.
That's why on Wednesday the fabless chip designer introduced what it's calling the Qualcomm AI Stack, which aims to, among other things, let developers take AI models they've developed for one device type, let's say smartphones, and easily adapt them for another, like PCs. This stack is only for devices powered by Qualcomm's system-on-chips, be they in laptops, cellphones, car entertainment, or something else.
While Qualcomm is best known for its mobile Arm-based Snapdragon chips that power many Android phones, the chip house is hoping to grow into other markets, such as personal computers, the Internet of Things, and automotive. This expansion means Qualcomm is competing with the likes of Apple, Intel, Nvidia, AMD, and others, on a much larger battlefield.
Analysis After re-establishing itself in the datacenter over the past few years, AMD is now hoping to become a big player in the AI compute space with an expanded portfolio of chips that cover everything from the edge to the cloud.
But as executives laid out during AMD's Financial Analyst Day 2022 event last week, the resurgent chip designer believes it has the right silicon and software coming into place to pursue the wider AI space.
Microsoft has pledged to clamp down on access to AI tools designed to predict emotions, gender, and age from images, and will restrict the usage of its facial recognition and generative audio models in Azure.
The Windows giant made the promise on Tuesday while also sharing its so-called Responsible AI Standard, a document [PDF] in which the US corporation vowed to minimize any harm inflicted by its machine-learning software. This pledge included assurances that the biz will assess the impact of its technologies, document models' data and capabilities, and enforce stricter use guidelines.
This is needed because – and let's just check the notes here – there are apparently not enough laws yet regulating machine-learning technology use. Thus, in the absence of this legislation, Microsoft will just have to force itself to do the right thing.
Comment More than 250 mass shootings have occurred in the US so far this year, and AI advocates think they have the solution. Not gun control, but better tech, unsurprisingly.
Machine-learning biz Kogniz announced on Tuesday it was adding a ready-to-deploy gun detection model to its computer-vision platform. The system, we're told, can detect guns seen by security cameras and send notifications to those at risk, notifying police, locking down buildings, and performing other security tasks.
In addition to spotting firearms, Kogniz uses its other computer-vision modules to notice unusual behavior, such as children sprinting down hallways or someone climbing in through a window, which could indicate an active shooter.
In brief US hardware startup Cerebras claims to have trained the largest AI model on a single device powered by the world's largest Wafer Scale Engine 2 chip the size of a plate.
"Using the Cerebras Software Platform (CSoft), our customers can easily train state-of-the-art GPT language models (such as GPT-3 and GPT-J) with up to 20 billion parameters on a single CS-2 system," the company claimed this week. "Running on a single CS-2, these models take minutes to set up and users can quickly move between models with just a few keystrokes."
The CS-2 packs a whopping 850,000 cores, and has 40GB of on-chip memory capable of reaching 20 PB/sec memory bandwidth. The specs on other types of AI accelerators and GPUs pale in comparison, meaning machine learning engineers have to train huge AI models with billions of parameters across more servers.
In Brief No, AI chatbots are not sentient.
Just as soon as the story on a Google engineer, who blew the whistle on what he claimed was a sentient language model, went viral, multiple publications stepped in to say he's wrong.
The debate on whether the company's LaMDA chatbot is conscious or has a soul or not isn't a very good one, just because it's too easy to shut down the side that believes it does. Like most large language models, LaMDA has billions of parameters and was trained on text scraped from the internet. The model learns the relationships between words, and which ones are more likely to appear next to each other.
Zscaler is growing the machine-learning capabilities of its zero-trust platform and expanding it into the public cloud and network edge, CEO Jay Chaudhry told devotees at a conference in Las Vegas today.
Along with the AI advancements, Zscaler at its Zenith 2022 show in Sin City also announced greater integration of its technologies with Amazon Web Services, and a security management offering designed to enable infosec teams and developers to better detect risks in cloud-native applications.
In addition, the biz also is putting a focus on the Internet of Things (IoT) and operational technology (OT) control systems as it addresses the security side of the network edge. Zscaler, for those not aware, makes products that securely connect devices, networks, and backend systems together, and provides the monitoring, controls, and cloud services an organization might need to manage all that.
The venture capital arm of Samsung has cut a check to help Israeli inference chip designer NeuReality bring its silicon dreams a step closer to reality.
NeuReality announced Monday it has raised an undisclosed amount of funding from Samsung Ventures, adding to the $8 million in seed funding it secured last year to help it get started.
As The Next Platform wrote in 2021, NeuReality is hoping to stand out with an ambitious system-on-chip design that uses what the upstart refers to as a hardware-based "AI hypervisor."
In the latest episode of Black Mirror, a vast megacorp sells AI software that learns to mimic the voice of a deceased woman whose husband sits weeping over a smart speaker, listening to her dulcet tones.
Only joking – it's Amazon, and this is real life. The experimental feature of the company's virtual assistant, Alexa, was announced at an Amazon conference in Las Vegas on Wednesday.
Rohit Prasad, head scientist for Alexa AI, described the tech as a means to build trust between human and machine, enabling Alexa to "make the memories last" when "so many of us have lost someone we love" during the pandemic.
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