...has nobody named Stanley.
What a shame.
Developers can create large datasets of synthetic videos to train computer-vision models using software written by a team of researchers led by Google. Data is one of the most important ingredients of deep learning. You need good quality samples in large quantities to boost a model's performance, though datasets of this ilk …
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.
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.
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.
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.
Opinion The Turing test is about us, not the bots, and it has failed.
Fans of the slow burn mainstream media U-turn had a treat last week.
On Saturday, the news broke that Blake Lemoine, a Google engineer charged with monitoring a chatbot called LaMDA for nastiness, had been put on paid leave for revealing confidential information.
Google has placed one of its software engineers on paid administrative leave for violating the company's confidentiality policies.
Since 2021, Blake Lemoine, 41, had been tasked with talking to LaMDA, or Language Model for Dialogue Applications, as part of his job on Google's Responsible AI team, looking for whether the bot used discriminatory or hate speech.
LaMDA is "built by fine-tuning a family of Transformer-based neural language models specialized for dialog, with up to 137 billion model parameters, and teaching the models to leverage external knowledge sources," according to Google.
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.
China's government has outlined its vision for digital services, expected behavior standards at China's big tech companies, and how China will put data to work everywhere – with president Xi Jinping putting his imprimatur to some of the policies.
Xi's remarks were made in his role as director of China’s Central Comprehensively Deepening Reforms Commission, which met earlier this week. The subsequent communiqué states that at the meeting Xi called for "financial technology platform enterprises to return to their core business" and "support platform enterprises in playing a bigger role in serving the real economy and smoothing positive interplay between domestic and international economic flows."
The remarks outline an attempt to balance Big Tech's desire to create disruptive financial products that challenge monopolies, against efforts to ensure that only licensed and regulated entities offer financial services.
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