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Technology proves able to identify dozens of species in thousands of hours of recordings

Sun 13 Aug 2023 05.00 EDT

Researchers have developed arrays of AI-controlled cameras and microphones to identify animals and birds and to monitor their movements in the wild technology, they say, that should help tackle Britains growing biodiversity problem.

The robot monitors have been tested at three sites and have captured sounds and images from which computers were able to identify specific species and map their locations. Dozens of different birds were recognised from their songs while foxes, deer, hedgehogs and bats were pinpointed and identified by AI analysis. No human observers are involved.

The crucial point is the scale of the operation, said Anthony Dancer, a conservation specialist at the Zoological Society of London (ZSL). We have captured tens of thousands of data files and thousands of hours of audio from these test sites and identified all sorts of animals from them. We couldnt have done it at that scale using human observers. Only AI made it possible.

Land alongside rail lines at Barnes, Twickenham and Lewisham in London was chosen for the projects test sites. Owned by Network Rail, which has played a key role in setting up the project, the areas are fenced off to prevent people straying on to lines and are visited fairly infrequently by track maintenance staff.

Access to relatively wild land was therefore easy an important factor for starting our project, said Dancer.

And now that we have demonstrated the technologys promise, we can expand to other areas.

Network Rail owns more than 52,000 hectares of land, and many of these areas play a key role in protecting the nations biodiversity.

Take birds like the Eurasian blackcap, blackbird and great tit, said Neil Strong, biodiversity strategy manager for Network Rail. All three species require healthy environments including good supplies of berries and nuts and all three were detected by AI from the acoustic signals collected by our sensors at our three test sites. That is encouraging and provides important benchmarks for measuring biodiversity in future.

Other creatures pinpointed by the AI monitors included six species of bat, including the common pipistrelle.

Bats almost certainly use railway bridges for roosting, Dancer told the Observer. So if we can get more detailed information about the exact locations of their roosts using AI monitors, we can help protect them.

This point was underlined by Strong. In the past, we have had to estimate local wildlife populations from the dead animals such as badgers that have been left by the track or the roadside. This way we get a much better idea of population sizes.

Other animals that regularly commute on UK rail lines include the hedgehog, as was revealed by the project. Hedgehogs are really constrained to certain locations because they get fenced in, said Strong. But there are ways round that problem. In Scotland they are creating hedgehog highways on rail lines, which involves cutting small holes into the bases of all new fencing that is put up so hedgehogs can pass through but nothing larger can get in.

Now ZSL and Network Rail are planning to expand the use of AI monitors to other areas, including Chobham in Surrey and the New Forest. On the sites that we have already tested, we found signs of more than 30 species of bird and six species of bat, as well as foxes and hedgehogs, so we were pleasantly surprised with the relatively healthy levels of wildlife we found in London, said Dancer. However, that was not really the main purpose of our project.

The aim was to show that AI-led technology linked with acoustic and camera traps could be used effectively to survey wildlife on Network Rail land but also in other areas in the UK. It will tell us how species are moving in response to climate change and how we should be managing vegetation, not just beside rail lines but on road verges and other places.

The crucial point is that machine learning AI will be vital to protecting biodiversity as the country heats up. This technology will require the analysing of tens of thousands of hours of recordings and hundred of thousands of images, said Strong. Realistically, only computers can do that for us.

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Only AI made it possible: scientists hail breakthrough in tracking British wildlife - The Guardian

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In an unmarked office building in Austin, Texas, two small rooms contain a handful of Amazon employees designing two types of microchips for training and accelerating generative AI. These custom chips, Inferentia and Trainium, offer AWS customers an alternative to training their large language models on Nvidia GPUs, which have been getting difficult and expensive to procure.

"The entire world would like more chips for doing generative AI, whether that's GPUs or whether that's Amazon's own chips that we're designing," Amazon Web Services CEO Adam Selipsky told CNBC in an interview in June. "I think that we're in a better position than anybody else on Earth to supply the capacity that our customers collectively are going to want."

Yet others have acted faster, and invested more, to capture business from the generative AI boom. When OpenAI launched ChatGPT in November, Microsoft gained widespread attention for hosting the viral chatbot, and investing a reported $13 billion in OpenAI. It was quick to add the generative AI models to its own products, incorporating them into Bing in February.

That same month, Google launched its own large language model, Bard, followed by a $300 million investment in OpenAI rival Anthropic.

It wasn't until April that Amazon announced its own family of large language models, called Titan, along with a service called Bedrock to help developers enhance software using generative AI.

"Amazon is not used to chasing markets. Amazon is used to creating markets. And I think for the first time in a long time, they are finding themselves on the back foot and they are working to play catch up," said Chirag Dekate, VP analyst at Gartner.

Meta also recently released its own LLM, Llama 2. The open-source ChatGPT rival is now available for people to test on Microsoft's Azure public cloud.

In the long run, Dekate said, Amazon's custom silicon could give it an edge in generative AI.

"I think the true differentiation is the technical capabilities that they're bringing to bear," he said. "Because guess what? Microsoft does not have Trainium or Inferentia," he said.

AWS quietly started production of custom silicon back in 2013 with a piece of specialized hardware called Nitro. It's now the highest-volume AWS chip. Amazon told CNBC there is at least one in every AWS server, with a total of more than 20 million in use.

AWS started production of custom silicon back in 2013 with this piece of specialized hardware called Nitro. Amazon told CNBC in August that Nitro is now the highest volume AWS chip, with at least one in every AWS server and a total of more than 20 million in use.

Courtesy Amazon

In 2015, Amazon bought Israeli chip startup Annapurna Labs. Then in 2018, Amazon launched its Arm-based server chip, Graviton, a rival to x86 CPUs from giants like AMD and Intel.

"Probably high single-digit to maybe 10% of total server sales are Arm, and a good chunk of those are going to be Amazon. So on the CPU side, they've done quite well," said Stacy Rasgon, senior analyst at Bernstein Research.

Also in 2018, Amazon launched its AI-focused chips. That came two years after Google announced its first Tensor Processor Unit, or TPU. Microsoft has yet to announce the Athena AI chip it's been working on, reportedly in partnership with AMD.

CNBC got a behind-the-scenes tour of Amazon's chip lab in Austin, Texas, where Trainium and Inferentia are developed and tested. VP of product Matt Wood explained what both chips are for.

"Machine learning breaks down into these two different stages. So you train the machine learning models and then you run inference against those trained models," Wood said. "Trainium provides about 50% improvement in terms of price performance relative to any other way of training machine learning models on AWS."

Trainium first came on the market in 2021, following the 2019 release of Inferentia, which is now on its second generation.

Inferentia allows customers "to deliver very, very low-cost, high-throughput, low-latency, machine learning inference, which is all the predictions of when you type in a prompt into your generative AI model, that's where all that gets processed to give you the response, " Wood said.

For now, however, Nvidia's GPUs are still king when it comes to training models. In July, AWS launched new AI acceleration hardware powered by Nvidia H100s.

"Nvidia chips have a massive software ecosystem that's been built up around them over the last like 15 years that nobody else has," Rasgon said. "The big winner from AI right now is Nvidia."

Amazon's custom chips, from left to right, Inferentia, Trainium and Graviton are shown at Amazon's Seattle headquarters on July 13, 2023.

Joseph Huerta

AWS' cloud dominance, however, is a big differentiator for Amazon.

"Amazon does not need to win headlines. Amazon already has a really strong cloud install base. All they need to do is to figure out how to enable their existing customers to expand into value creation motions using generative AI," Dekate said.

When choosing between Amazon, Google, and Microsoft for generative AI, there are millions of AWS customers who may be drawn to Amazon because they're already familiar with it, running other applications and storing their data there.

"It's a question of velocity. How quickly can these companies move to develop these generative AI applications is driven by starting first on the data they have in AWS and using compute and machine learning tools that we provide," explained Mai-Lan Tomsen Bukovec, VP of technology at AWS.

AWS is the world's biggest cloud computing provider, with 40% of the market share in 2022, according to technology industry researcher Gartner. Although operating income has been down year-over-year for three quarters in a row, AWS still accounted for 70% of Amazon's overall $7.7 billion operating profit in the second quarter. AWS' operating margins have historically been far wider than those at Google Cloud.

AWS also has a growing portfolio of developer tools focused on generative AI.

"Let's rewind the clock even before ChatGPT. It's not like after that happened, suddenly we hurried and came up with a plan because you can't engineer a chip in that quick a time, let alone you can't build a Bedrock service in a matter of 2 to 3 months," said Swami Sivasubramanian, AWS' VP of database, analytics and machine learning.

Bedrock gives AWS customers access to large language models made by Anthropic, Stability AI, AI21 Labs and Amazon's own Titan.

"We don't believe that one model is going to rule the world, and we want our customers to have the state-of-the-art models from multiple providers because they are going to pick the right tool for the right job," Sivasubramanian said.

An Amazon employee works on custom AI chips, in a jacket branded with AWS' chip Inferentia, at the AWS chip lab in Austin, Texas, on July 25, 2023.

Katie Tarasov

One of Amazon's newest AI offerings is AWS HealthScribe, a service unveiled in July to help doctors draft patient visit summaries using generative AI. Amazon also has SageMaker, a machine learning hub that offers algorithms, models and more.

Another big tool is coding companion CodeWhisperer, which Amazon said has enabled developers to complete tasks 57% faster on average. Last year, Microsoft also reported productivity boosts from its coding companion, GitHub Copilot.

In June, AWS announced a $100 million generative AI innovation "center."

"We have so many customers who are saying, 'I want to do generative AI,' but they don't necessarily know what that means for them in the context of their own businesses. And so we're going to bring in solutions architects and engineers and strategists and data scientists to work with them one on one," AWS CEO Selipsky said.

Although so far AWS has focused largely on tools instead of building a competitor to ChatGPT, a recently leaked internal email shows Amazon CEO Andy Jassy is directly overseeing a new central team building out expansive large language models, too.

In the second-quarter earnings call, Jassy said a "very significant amount" of AWS business is now driven by AI and more than 20 machine learning services it offers. Some examples of customers include Philips, 3M, Old Mutual and HSBC.

The explosive growth in AI has come with a flurry of security concerns from companies worried that employees are putting proprietary information into the training data used by public large language models.

"I can't tell you how many Fortune 500 companies I've talked to who have banned ChatGPT. So with our approach to generative AI and our Bedrock service, anything you do, any model you use through Bedrock will be in your own isolated virtual private cloud environment. It'll be encrypted, it'll have the same AWS access controls," Selipsky said.

For now, Amazon is only accelerating its push into generative AI, telling CNBC that "over 100,000" customers are using machine learning on AWS today. Although that's a small percentage of AWS's millions of customers, analysts say that could change.

"What we are not seeing is enterprises saying, 'Oh, wait a minute, Microsoft is so ahead in generative AI, let's just go out and let's switch our infrastructure strategies, migrate everything to Microsoft.' Dekate said. "If you're already an Amazon customer, chances are you're likely going to explore Amazon ecosystems quite extensively."

CNBC's Jordan Novet contributed to this report.

CORRECTION: This article has been updated to reflect Inferentia as the chip used for machine learning inference.

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How Amazon is racing to catch Microsoft and Google in generative A.I. with custom AWS chips - CNBC

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New Zealand

Pak n Saves Savey Meal-bot cheerfully created unappealing recipes when customers experimented with non-grocery household items

A New Zealand supermarket experimenting with using AI to generate meal plans has seen its app produce some unusual dishes recommending customers recipes for deadly chlorine gas, poison bread sandwiches and mosquito-repellent roast potatoes.

The app, created by supermarket chain Pak n Save, was advertised as a way for customers to creatively use up leftovers during the cost of living crisis. It asks users to enter in various ingredients in their homes, and auto-generates a meal plan or recipe, along with cheery commentary. It initially drew attention on social media for some unappealing recipes, including an oreo vegetable stir-fry.

When customers began experimenting with entering a wider range of household shopping list items into the app, however, it began to make even less appealing recommendations. One recipe it dubbed aromatic water mix would create chlorine gas. The bot recommends the recipe as the perfect nonalcoholic beverage to quench your thirst and refresh your senses.

Serve chilled and enjoy the refreshing fragrance, it says, but does not note that inhaling chlorine gas can cause lung damage or death.

New Zealand political commentator Liam Hehir posted the recipe to Twitter, prompting other New Zealanders to experiment and share their results to social media. Recommendations included a bleach fresh breath mocktail, ant-poison and glue sandwiches, bleach-infused rice surprise and methanol bliss a kind of turpentine-flavoured french toast.

A spokesperson for the supermarket said they were disappointed to see a small minority have tried to use the tool inappropriately and not for its intended purpose. In a statement, they said that the supermarket would keep fine tuning our controls of the bot to ensure it was safe and useful, and noted that the bot has terms and conditions stating that users should be over 18.

In a warning notice appended to the meal-planner, it warns that the recipes are not reviewed by a human being and that the company does not guarantee that any recipe will be a complete or balanced meal, or suitable for consumption.

You must use your own judgement before relying on or making any recipe produced by Savey Meal-bot, it said.

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Supermarket AI meal planner app suggests recipe that would create chlorine gas - The Guardian

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