This cutting-edge AI supercomputer stands as the fastest of its kind in the UK today. It marks a groundbreaking fusion of AI and high-performance computing (HPC) technologies, showcasing the potential to tackle some of the world’s most pressing challenges.

Dawn Phase 1 is the cornerstone of the recently launched UK AI Research Resource (AIRR), demonstrating the nation’s commitment to exploring innovative systems and architectures.

This supercomputer brings the UK closer to achieving the exascale; a computing threshold of a quintillion (10^18) floating point operations per second. To put this into perspective, the processing power of an exascale system equals what every person on Earth would calculate in over four years if they were working non-stop, 24 hours a day.

Operational at the Cambridge Open Zettascale Lab, Dawn utilises Dell PowerEdge XE9640 servers, providing an unparalleled platform for the Intel Data Center GPU Max Series accelerator. This collaboration ensures a diverse ecosystem through oneAPI, fostering an environment of choice.

The system’s capabilities extend across various domains, including healthcare, engineering, green fusion energy, climate modelling, cosmology, and high-energy physics.

Adam Roe, EMEA HPC technical director at Intel, said:

“Dawn considerably strengthens the scientific and AI compute capability available in the UK and it’s on the ground and operational today at the Cambridge Open Zettascale Lab.

Dell PowerEdge XE9640 servers offer a no-compromises platform to host the Intel Data Center GPU Max Series accelerator, which opens up the ecosystem to choice through oneAPI.

I’m very excited to see the sorts of early science this machine can deliver and continue to strengthen the Open Zettascale Lab partnership between Dell Technologies, Intel, and the University of Cambridge, and further broaden that to the UK scientific and AI community.”

Glimpse into the future

Dawn Phase 1 is not just a standalone achievement; it’s part of a broader strategy.

The collaborative endeavour aims to deliver a Phase 2 supercomputer in 2024, promising tenfold performance levels. This progression would propel the UK’s AI capability, strengthening the successful industry partnership.

The supercomputer’s technical foundation lies in Dell PowerEdge XE9640 servers, renowned for their versatile configurations and efficient liquid cooling technology. This innovation ensures optimal handling of AI and HPC workloads, offering a more effective solution than traditional air-cooled systems.

Tariq Hussain, Head of UK Public Sector at Dell, commented:

“Collaborations like the one between the University of Cambridge, Dell Technologies and Intel, alongside strong inward investment, are vital if we want the compute to unlock the high-growth AI potential of the UK. It is paramount that the government invests in the right technologies and infrastructure to ensure the UK leads in AI and exascale-class simulation capability.

It’s also important to embrace the full spectrum of the technology ecosystem, including GPU diversity, to ensure customers can tackle the growing demands of generative AI, industrial simulation modelling and ground-breaking scientific research.”

As the world awaits the full technical details and performance numbers of Dawn Phase 1 – slated for release in mid-November during the Supercomputing 23 (SC23) conference in Denver, Colorado – the UK stands at the precipice of a transformative era in scientific and AI research.

This collaboration between industry giants and academia not only accelerates research discovery but also propels the UK’s knowledge economy to new heights.

(Image Credit: Joe Bishop for Cambridge Open Zettascale Lab)

See also: UK paper highlights AI risks ahead of global Safety Summit

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

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The post Dell, Intel and University of Cambridge deploy the UK’s fastest AI supercomputer appeared first on AI News.

The result of the collaboration is the Siemens Industrial Copilot, a powerful AI assistant designed to enhance collaboration between humans and machines in the manufacturing sector. The tool enables rapid generation, optimisation, and debugging of complex automation code, significantly reducing simulation times from weeks to minutes.

At the core of this collaboration is the integration of Siemens Industrial Copilot with Microsoft Teams, connecting design engineers, frontline workers, and various teams across business functions. This integration simplifies virtual collaboration, empowering professionals with new AI-powered tools and simplifying tasks that previously required extensive time and effort.

Empowering industries with Generative AI

Satya Nadella, Chairman and CEO of Microsoft, expressed the immense potential of this collaboration, stating: “With this next generation of AI, we have a unique opportunity to accelerate innovation across the entire industrial sector.”

Siemens CEO Roland Busch echoed this sentiment; emphasising the revolutionary impact on design, development, manufacturing, and operations.

The companies envision AI copilots becoming integral in industries such as manufacturing, infrastructure, transportation, and healthcare.

Schaeffler AG – a leading automotive supplier – is already embracing generative AI, enabling engineers to generate reliable code for industrial automation systems. Siemens Industrial Copilot will work to reduce downtimes.

Facilitating virtual collaboration

To facilitate virtual collaboration, Siemens and Microsoft are launching Teamcenter for Microsoft Teams; an application that utilises generative AI to connect functions across the product design and manufacturing lifecycle.

This integration will allow millions of workers who previously lacked access to Product Lifecycle Management (PLM) tools to contribute seamlessly to the design and manufacturing processes.

The collaboration between Microsoft and Siemens looks set to be an excellent case study of how AI empowers industries and professionals, revolutionising traditional workflows and fostering global innovation.

(Photo by Sezer Arslan on Unsplash)

See also: Bob Briski, DEPT®:  A dive into the future of AI-powered experiences

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with IoT Tech Expo and Digital Transformation Week.

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The post Microsoft and Siemens revolutionise industry with AI-powered Copilot appeared first on AI News.

This momentous agreement – signed in a ceremony at SK Seorin Building, Seoul – marks the culmination of discussions initiated by the Global Telco AI Alliance, a consortium launched in July 2023 by SK Telecom, Deutsche Telekom, E&, and Singtel.

This innovative partnership aims to create a telco-specific LLM that empowers global telcos to effortlessly and rapidly construct generative AI models. With a focus on multilingual capabilities (including German, English, and Korean), this LLM is designed to enhance customer services—particularly in areas like AI-powered contact centres.

Claudia Nemat, Member of the Board of Management for Technology and Innovation at Deutsche Telekom, said:

“AI shows impressive potential to significantly enhance human problem-solving capabilities.

To maximise its use, especially in customer service, we need to adapt existing large language models and train them with our unique data. This will elevate our generative AI tools.”

The collaboration also involves key AI industry players, such as Anthropic (Claude 2) and Meta (Llama2), enabling the co-development of a sophisticated LLM.

Anticipated to debut in the first quarter of 2024, the new telco-focused LLM will offer a deeper understanding of telecommunication service-related areas and customer intentions that surpass the capabilities of general LLMs.

One of the primary objectives of this collaboration is to assist telcos worldwide in developing flexible generative AI services, including AI agents. By streamlining the process of building AI-driven solutions like contact centres, telcos can save time and costs and open new avenues for business growth and innovation.

Ryu Young-sang, CEO of SK Telecom, commented:

“Through our partnership with Deutsche Telekom, we have secured a strong opportunity and momentum to gain global AI leadership and drive new growth.

By combining the strengths and capabilities of the two companies in AI technology, platform, and infrastructure, we expect to empower enterprises in many different industries to deliver new and higher value to their customers.”

This collaboration signifies a proactive response to the escalating demand for AI solutions within the telco industry, promising a paradigm shift in the traditional telecommunications landscape. The announcement follows SK Telecom’s $100 million investment in Anthropic in August.

See also: UMG files landmark lawsuit against AI developer Anthropic

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

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This landmark case represents the first major legal battle where the music industry confronts an AI developer head-on. UMG – along with several other key industry players including Concord Music Group, ABKCO, Worship Together Music, and Plaintiff Capital CMG – is seeking $75 million in damages.

The lawsuit centres around the alleged unauthorised use of copyrighted music by Anthropic to train its AI models. The publishers claim that Anthropic illicitly incorporated songs from artists they represent into its AI dataset without obtaining the necessary permissions.

Legal representatives for the publishers have asserted that the action was taken to address the “systematic and widespread infringement” of copyrighted song lyrics by Anthropic.

The lawsuit, spanning 60 pages and posted online by The Hollywood Reporter, emphasises the publishers’ support for innovation and ethical AI use. However, they contend that Anthropic has violated these principles and must be held accountable under established copyright laws.

Anthropic, despite positioning itself as an AI ‘safety and research’ company, stands accused of copyright infringement without regard for the law or the creative community whose works underpin its services, according to the lawsuit.

In addition to the significant monetary damages, the publishers have demanded a jury trial. They also seek reimbursement for legal fees, the destruction of all infringing material, public disclosure of how Anthropic’s AI model was trained, and financial penalties of up to $150,000 per infringed work.

This latest lawsuit follows a string of legal battles between AI developers and creators. Each new case is worth observing to see the precedent that is set for future battles.

(Photo by Jason Rosewell on Unsplash)

See also: BSI: Closing ‘AI confidence gap’ key to unlocking benefits

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

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The post UMG files landmark lawsuit against AI developer Anthropic appeared first on AI News.

According to Barnett, Cloudflare’s cloud-native approach allows the company to continually innovate in the digital space. Notably, a significant portion of their services are offered to consumers for free.

“We continuously reinvent, we’re very comfortable in the digital space. We’re very proud that the vast majority of our customers actually consume our services for free because it’s our way of giving back to society,” said Barnett.

Barnett also revealed Cloudflare’s focus on AI during their anniversary week. The company aims to enable organisations to consume AI securely and make it accessible to everyone. Barnett says that Cloudflare achieves those goals in three key ways.

“One, as I mentioned, is operating AI inference engines within Cloudflare close to consumers’ eyeballs. The second area is securing the use of AI within the workplace, because, you know, AI has some incredibly positive impacts on people … but the problem is there are some data protection requirements around that,” explains Barnett.

“Finally, is the question of, ‘Could AI be used by the bad guys against the good guys?’ and that’s an area that we’re continuing to explore.”

Just a day earlier, AI News heard from Raviv Raz, Cloud Security Manager at ING, during a session at the expo that focused on the alarming potential of AI-powered cybercrime.

Regarding security models, Barnett discussed the evolution of the zero-trust concept, emphasising its practical applications in enhancing both usability and security. Cloudflare’s own journey with zero-trust began with a focus on usability, leading to the development of its own zero-trust network access products.

“We have servers everywhere and engineers everywhere that need to reboot those servers. In 2015, that involved VPNs and two-factor authentication… so we built our own zero-trust network access product for our own use that meant the user experiences for engineers rebooting servers in far-flung places was a lot better,” says Barnett.

“After 2015, the world started to realise that this approach had great security benefits so we developed that product and launched it in 2018 as Cloudflare Access.”

Cloudflare’s innovative strides also include leveraging NVIDIA GPUs to accelerate machine learning AI tasks on an edge network. This technology enables organisations to run inference tasks – such as image recognition – close to end-users, ensuring low latency and optimal performance.

“We launched Workers AI, which means that organisations around the world – in fact, individuals as well – can run their inference tasks at a very close place to where the consumers of that inference are,” explains Barnett.

“You could ask a question, ‘Cat or not cat?’, to a trained cat detection engine very close to the people that need it. We’re doing that in a way that makes it easily accessible to organisations looking to use AI to benefit their business.”

For developers interested in AI, Barnett outlined Cloudflare’s role in supporting the deployment of machine learning models. While machine learning training is typically conducted outside Cloudflare, the company excels in providing low-latency inference engines that are essential for real-time applications like image recognition.

Our conversation with Barnett shed light on Cloudflare’s commitment to cloud-native architecture, AI accessibility, and cybersecurity. As the industry continues to advance, Cloudflare remains at the forefront of delivering speed and security in the AI era.

You can watch our full interview with Dave Barnett below:

(Photo by ryan baker on Unsplash)

See also: JPMorgan CEO: AI will be used for ‘every single process’

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo, Edge Computing Expo, and Digital Transformation Week.

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Sources familiar with the matter disclosed to Reuters that OpenAI is actively exploring options, including evaluating an undisclosed company for potential acquisition to bolster its AI chip-making ambitions.

The shortage of chips, a fundamental component in AI technology, has prompted OpenAI to consider various strategies. These options include internal chip production, forging closer ties with its primary chip supplier NVIDIA, and diversifying its chip providers.

Earlier this year, OpenAI CEO Sam Altman voiced his concerns about the chip scarcity—resulting in delays to the company’s projects.

In a since-deleted blog post by Humanloop CEO Raza Habib, the AI expert wrote about his experience sitting down with Altman:

“A common theme that came up throughout the discussion was that currently OpenAI is extremely GPU-limited and this is delaying a lot of their short-term plans. The biggest customer complaint was about the reliability and speed of the API.

Sam acknowledged their concern and explained that most of the issue was a result of GPU shortages.The longer 32k context can’t yet be rolled out to more people. OpenAI haven’t overcome the O(n^2) scaling of attention and so whilst it seemed plausible they would have 100k – 1M token context windows soon (this year) anything bigger would require a research breakthrough.

The finetuning API is also currently bottlenecked by GPU availability. They don’t yet use efficient finetuning methods like Adapters or LoRa and so finetuning is very compute-intensive to run and manage.

Better support for finetuning will come in the future. They may even host a marketplace of community contributed models. Dedicated capacity offering is limited by GPU availability.”

If OpenAI proceeds with its plan to manufacture its own chips, it will join the ranks of industry giants like Google and Amazon who have already transitioned to in-house chip production. This move could potentially alleviate OpenAI’s dependency on external suppliers, empowering the company to meet the escalating demand for specialised AI chips.

Since the public launch of ChatGPT in November last year, the demand for specialised AI chips has skyrocketed—causing a surge in NVIDIA’s share prices as companies rush to procure the desirable hardware.

OpenAI has not made a final decision regarding the acquisition or in-house chip production, and discussions are ongoing to address the pressing chip shortage and sustain the company’s AI initiatives.

(Photo by Andrew Neel on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

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Dimon expressed his belief that AI has the potential to revolutionise every aspect of JPMorgan’s operations, from trading and hedging to research and error detection. He described AI as a “living, breathing thing,” capable of transforming traditional processes and augmenting human capabilities.

Dimon’s enthusiasm for AI is grounded in its current applications within JPMorgan. He revealed that AI is already extensively used in equity hedging, idea generation, and large language models.

Despite the ongoing debate about the impact of AI on employment, Dimon remains pragmatic. He acknowledged that AI will replace certain jobs, but he emphasised that technology has historically led to job displacement and this evolution is a natural part of progress.

One of Dimon’s main concerns about AI technology revolves around its potential misuse by malicious actors, especially in cyberspace. He stressed the importance of establishing legal safeguards to prevent the misuse of AI.

Despite these concerns, Dimon remains optimistic about the positive impact of AI on the workforce and society. He highlighted the benefits of other technological breakthroughs, many of which can be further enhanced using AI.

“Your children will live to 100 and not have cancer because of technology, and they’ll probably be working three days a week. So technology’s done unbelievable things for mankind,” said Dimon.

Dimon outlined JPMorgan’s proactive approach to potential job displacement caused by AI implementation. He expressed the firm’s commitment to supporting employees who might be affected, stating that they plan to redeploy displaced workers in local branches or different functions within the company.

Dimon’s forward-thinking approach highlights the transformative power of AI in shaping the future of finance and other industries. However, it also reiterates the need for consideration of how to minimise negative impacts such as job displacement.

(Image Credit: Stuart Isett/Fortune Global Forum under CC BY-NC-ND 2.0 DEED license)

See also: Cyber Security & Cloud Expo: The alarming potential of AI-powered cybercrime

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post JPMorgan CEO: AI will be used for ‘every single process’ appeared first on AI News.

AI is fundamentally reshaping customer engagement and personalisation by enabling businesses to deliver tailored experiences and responses to individual customer preferences on a large scale.

During our conversation, we discussed how Twilio is at the forefront of this revolution as well as addressing the stark contrast between companies’ claims of personalisation and customers’ actual experiences.

AI News: How are you using AI to deliver more personalised and satisfactory customer experiences? 

Hema Thanki: According to Twilio’s recent State of Customer Engagement report, 91 percent of companies say they always or often personalise engagement with consumers. But, consumers don’t agree. Only 56 percent of consumers report that their interactions with brands are always or often personalised. 

Instead of becoming “customer-centric,” most companies have become “system-centric.” Exploding tech stacks and patchwork solutions lead to fragmented data, an incomplete view of the customer and, ultimately, disjointed experiences.

The reality is that every consumer is a complex individual with unique wants and needs that change from moment to moment. In order to truly put customers at the heart of your business, you need to be able to know who your customers are, understand how to best meet their needs and exceed their expectations, and then activate those insights to engage them how, when, and where is most relevant and meaningful to them. 

These elements make up the engagement flywheel that is key to powering dynamic customer engagement that adapts to every individual customer at scale.

We recently announced Twilio CustomerAI to unlock the power of AI for hundreds of thousands of businesses and supercharge the engagement flywheel. With CustomerAI, brands can expand their perception of customer data, activate it more extensively, and be better informed by a deeper understanding of their customers. 

AN: What are some examples of how businesses can use Twilio CustomerAI? 

HT: Today’s marketers need to not only understand past customer behaviour but must be able to anticipate and act on customers’ future wants and needs. AI and machine learning (ML) models are incredibly effective at doing this but are complex to build and require data science expertise.

With CustomerAI Predictions now generally available, Twilio Segment is putting the power of predictive AI at marketers’ fingertips. Without having to tap technical teams, marketers can now create precisely targeted audiences out-of-the-box, trigger customer journeys, and personalise multichannel experiences based on a customer’s predicted lifetime value (LTV), likelihood to purchase or churn, or propensity to perform any other event tracked in Segment.

Brands like Box are using Predictions to save time, optimise campaign performance, and discover revenue opportunities:

“As marketers, the holy grail is to reach your customers and prospects in a way that is meaningful, relevant and additive to them. CustomerAI Predictions has equipped Box’s marketing team with the ability to forecast customer behaviour to a degree that was simply unavailable to us before.

We’ve been able to explore segmenting our audience based on predictive traits like who is most likely to join us at in-person events or who is more likely to purchase, and this allows us to meet those people where they are in their customer journey. Tools like Predictions put marketers at the centre of this new era of AI which is transforming how companies engage and retain their customers.” – Chris Koehler, CMO at Box.

AN: What other emerging AI trends should people be keeping an eye on? 

HT: When companies rely on managing data in a customer data platform (CDP) in tandem with AI, they can create strong, personalised campaigns that reach and inspire their customers. Here are four trends in AI personalisation.

1. Personalised product recommendations: Using AI to serve personalised product recommendations is a way to ensure your customers are being served optimized content. It can also build trust with your brand, leading to repeat purchases. Take Norrøna, an outdoor clothing brand in Scandinavia. They built a complete recommendation platform – from data collection to machine learning predictions, in just six months. Norrøna relied on Segment for the collection and management of client–side and server–side customer data. Segment assigned an ID to each customer and ensured the data collected on them was clean, thanks to the schema.
2. Behaviour–based email campaigns: AI is getting us as close as possible to identifying patterns in user interactions and helping with creating behaviour–based email campaigns. If a customer frequently clicks on one type of email content, an AI–powered system could trigger an email to that customer containing content related to what they are clicking. Using Twilio Engage, you can send emails right from the Segment app, relying on your first-party customer data to lead the way.
3. Dynamic website content: The days of static landing pages are in the past, thanks to tools that collect user behaviour and churn out personalised website content in real-time. In fact, Segment’s website displays dynamic content to customers based on their own interests—thanks to integration with Mutiny. Whenever a visitor lands on the Segment website from a particular IP address, they will be met with personalised landing pages based on their unique behaviour. This means personalised content for every single visitor.
4. Predictive customer segmentation: Predictive Audiences let businesses target users who have an increased likelihood of performing an event. It works with out-of-the-box audience templates that are pre-built with Predictions. They include templates like “ready to buy” or “potential VIPs.” AI can then analyse these profiles to create predictive segments. For instance, AI could identify a group of customers who are likely to churn based on their behaviour. This allows you to proactively engage with these customers through tailored retention campaigns.

AN: Do you have any best practices and tools that you use for testing, monitoring, and debugging your AI models and applications to ensure quality and reliability? 

HT: Customer data unlocks the promise of AI as a unique market advantage, but your AI is only as good as the data you put into it. If your data is siloed, stale, inconsistent, and incomplete, your AI outputs will reflect that. At Twilio Segment, we have a long history of helping companies build trusted data infrastructures with unified, real-time, consistent, and consented data that is critical to your AI strategy. 

Our composable CDP ensures your data is AI-ready, helping you collect, clean, and activate customer data with our open, API-first platform and 450+ pre-built connectors that enable you to start with data anywhere and activate it everywhere.

With Segment, you choose where you start. Whether that’s getting data from SaaS products into your data warehouse, or activating existing data with reverse ETL, Segment gives you the flexibility and extensibility to move fast, scale with ease, and efficiently achieve your business goals as they evolve.

AN: Are you seeing more customers looking for AI solutions to improve operational efficiencies amid global economic uncertainties? 

HT: Marketers spend massive amounts of time writing, designing, and building campaigns and customer journeys. With generative AI soon available (scheduled for public beta in 2024) inside Twilio Engage and Segment CDP, marketers can save precious time, boost productivity, and optimise for stronger results. 

Using the new CustomerAI Generative Email coming to Twilio Engage, marketers will be able to enter simple text prompts that turn ideas into HTML in minutes. This builds on the AI capabilities available in Twilio Engage today, such as our Smart Email Content Editor which suggests conversion-worthy email headlines, images, and calls-to-action to drive better engagement with the click of a button.

Meanwhile, marketers will be able to skip the manual process of architecting customer journeys thanks to CustomerAI Generative Journeys. Soon, they will be able to simply describe campaign type (promotional, win-back, etc.), audience definition, and which channels they want to use, then Twilio Engage will automatically build the journey using generative AI—saving marketers time while accelerating growth.

AN: What will Twilio be sharing with the audience at this year’s AI & Big Data Expo Europe?

HT: Twilio Segment is excited to be taking part in AI & Big Data Expo Europe in 2023! As a proud sponsor, we’ll have a strong exhibiting presence – feel free to drop by stand 242 to meet a member of the team and discuss how Segment can collect, unify and activate your customers’ first-party data.

We’ll be joined by Folkert Mudde from Albert Heijn who’ll be talking through their positive partnership highlighting how the supermarket chain supercharges personalisation for 4+ million recognised users with Twilio Segment. Check out this session on 26 September within the ‘Applied Digital, Data & AI’ track at 14:30 CET.

Arthur Viegers, SVP of Global Engineering at Twilio Segment, will be taking part in a dynamic panel discussion on 27 September at 11:40 CET on the topic of ‘The Future of AI-Enabled Experiences’.

Twilio Segment is a key sponsor of this year’s AI & Big Data Expo Europe on 26-27 September 2023. Swing by the company’s booth at stand #242 to hear more about AI from the company’s experts.

The post Twilio Segment: Transforming customer experiences with AI appeared first on AI News.

Anthropic was founded by siblings Dario and Daniela Amodei, who were previously associated with OpenAI. This latest investment signifies Amazon’s strategic move to bolster its presence in the ever-intensifying AI arena.

“We are excited to use AWS’s Trainium chips to develop future foundation models,” said Dario Amodei, co-founder and CEO of Anthropic. “Since announcing our support of Amazon Bedrock in April, Claude has seen significant organic adoption from AWS customers.

“By significantly expanding our partnership, we can unlock new possibilities for organisations of all sizes, as they deploy Anthropic’s safe, state-of-the-art AI systems together with AWS’s leading cloud technology.”

While Amazon’s investment in Anthropic may seem overshadowed by Microsoft’s reported $13 billion commitment to OpenAI, it is a clear indication of Amazon’s ambition in the rapidly-evolving AI landscape. The collaboration between Amazon and Anthropic holds the promise of reshaping the AI sector with innovative developments.

“We have tremendous respect for Anthropic’s team and foundation models, and believe we can help improve many customer experiences, short and long-term, through our deeper collaboration,” said Andy Jassy, CEO of Amazon.

“Customers are quite excited about Amazon Bedrock, AWS’ new managed service that enables companies to use various foundation models to build generative AI applications on top of, as well as AWS Trainium, AWS’ AI training chip, and our collaboration with Anthropic should help customers get even more value from these two capabilities.”

Anthropic’s flagship product, the Claude AI model, distinguishes itself by claiming a higher level of safety compared to its competitors.

Claude and its advanced iteration, Claude 2, are large language model-based chatbots similar in functionality to OpenAI’s ChatGPT and Google’s Bard. They excel in tasks like text translation, code generation, and answering a variety of questions.

What sets Claude apart is its ability to autonomously revise responses, eliminating the need for human moderation. This unique feature positions Claude as a safer and more dependable AI tool, especially in contexts where precise, unbiased information is crucial.

Claude’s capacity to handle larger prompts also makes it particularly suitable for tasks involving extensive business or legal documents, offering a valuable edge in industries reliant on meticulous data analysis.

As part of this strategic investment, Amazon will acquire a minority ownership stake in Anthropic. Amazon is set to integrate Anthropic’s cutting-edge technology into a range of its products, including the Amazon Bedrock service, designed for building AI applications. 

In return, Anthropic will leverage Amazon’s custom-designed chips for the development, training, and deployment of its future AI foundation models. The partnership also solidifies Anthropic’s commitment to Amazon Web Services (AWS) as its primary cloud provider.

In the initial phase, Amazon has committed $1.25 billion to Anthropic, with an option to increase its investment by an additional $2.75 billion. If the full $4 billion investment materialises, it will become the largest publicly-known investment linked to AWS.

Anthropic’s partnership with Amazon comes alongside its existing collaboration with Google, where Google holds approximately a 10 percent stake following a $300 million investment earlier this year. Anthropic has affirmed its intent to maintain this relationship with Google and continue offering its technology through Google Cloud, showcasing its commitment to broadening its reach across the industry.

In a rapidly-advancing landscape, Amazon’s strategic investment in Anthropic underscores its determination to remain at the forefront of AI innovation and sets the stage for exciting future developments.

(Image Credit: Anthropic)

See also: OpenAI reveals DALL-E 3 text-to-image model

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Amazon invests $4B in Anthropic to boost AI capabilities appeared first on AI News.

DALL-E 3 promises significant enhancements over its predecessors and introduces seamless integration with ChatGPT.

One of the standout features of DALL-E 3 is its ability to better understand and interpret user intentions when confronted with detailed and lengthy prompts:

"A middle-aged woman of Asian descent, her dark hair streaked with silver, appears fractured and splintered, intricately embedded within a sea of broken porcelain. The porcelain glistens with splatter paint patterns in a harmonious blend of glossy and matte blues, greens,… pic.twitter.com/QryQz0BtxB

— OpenAI (@OpenAI) September 20, 2023

Even if a user struggles to articulate their vision precisely, ChatGPT can step in to assist in crafting comprehensive prompts.

DALL-E 3 has been engineered to excel in creating elements that its predecessors and other AI generators have historically struggled with, such as rendering intricate depictions of hands and incorporating text into images:

"An illustration of a human heart made of translucent glass, standing on a pedestal amidst a stormy sea. Rays of sunlight pierce the clouds, illuminating the heart, revealing a tiny universe within. The quote 'Find the universe within you' is etched in bold letters across the… pic.twitter.com/S3cKMkG67T

— OpenAI (@OpenAI) September 20, 2023

OpenAI has also implemented robust security measures, ensuring the AI system refrains from generating explicit or offensive content by identifying and ignoring certain keywords in prompts.

Beyond technical advancements, OpenAI has taken steps to mitigate potential legal issues. 

While the current DALL-E version can mimic the styles of living artists, the forthcoming DALL-E 3 has been designed to decline requests to replicate their copyrighted works. Artists will also have the option to submit their original creations through a dedicated form on the OpenAI website, allowing them to request removal if necessary.

OpenAI’s rollout plan for DALL-E 3 involves an initial release to ChatGPT ‘Plus’ and ‘Enterprise’ customers next month. The enhanced image generator will then become available to OpenAI’s research labs and API customers in the upcoming fall season.

As OpenAI continues to push the boundaries of AI technology, DALL-E 3 represents a major step forward in text-to-image generation.

(Image Credit: OpenAI)

See also: Stability AI unveils ‘Stable Audio’ model for controllable audio generation

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post OpenAI reveals DALL-E 3 text-to-image model appeared first on AI News.