Various news outlets have been keeping tabs on OpenAI's CEO—Sam Altman—the AI technology evangelist was reported to be pursuing an ambitious proprietary AI chip project in early 2024. Inside sources pointed to late-January negotiations with important investment personnel in the Middle East—many believe that OpenAI leadership is exploring the idea of establishing its own network of semiconductor production plants. Late last week, The Wall Street Journal followed up on last month's AI industry rumors: "(Altman) has another great ambition: raising trillions of dollars to reshape the global semiconductor industry. The OpenAI chief executive officer is in talks with investors including the United Arab Emirates government to raise funds for a wildly ambitious tech initiative that would boost the world's chip-building capacity, expand its ability to power AI." One anonymous insider reckons that "the project could require raising as much as $5 trillion to $7 trillion."

TSMC is reportedly in the equation—Altman allegedly conducted talks with top brass last month—their expertise in cutting edge fabrication techniques would be of great value, although it is somewhat futile to reveal too many industry secrets given the sheer scale of OpenAI's (reported) aggressive expansion plans. The Wall Street Journal (WSJ) suggests that the embryonic venture is far more "open" than previously reported—a collaborative venture could be established once funding is secured, although Altman & Co. face "significant obstacles" en route. WSJ proposes that the somewhat OpenAI-centric fabrication network is best founded by a joint partnership—involving multiple investors, contract chip manufacturers (perhaps TSMC), and energy/power providers. OpenAI appears to be the "primary buyer" of resultant fabricated AI chips, with manufacturing services also offered to other clients. The scale of such an endeavor is put into perspective by WSJ's analysis (via inside sources): "Such a sum of investment would dwarf the current size of the global semiconductor industry. Global sales of chips were $527 billion last year and are expected to rise to $1 trillion annually by 2030. Global sales of semiconductor manufacturing equipment—the costly machinery needed to run chip factories—last year were $100 billion, according to an estimate by the industry group SEMI."

OpenAI is reported to be initiating R&D on a proprietary AI processing solution—the research organization's CEO, Sam Altman, has commented on the in-efficient operation of datacenters running NVIDIA H100 and A100 GPUs. He foresees a future scenario where his company becomes less reliant on Team Green's off-the-shelf AI-crunchers, with a deployment of bespoke AI processors. A short Reuters interview also underlined Altman's desire to find alternatives sources of power: "It motivates us to go invest more in (nuclear) fusion." The growth of artificial intelligence industries has put an unprecedented strain on energy providers, so tech firms could be semi-forced into seeking out frugal enterprise hardware.

The Financial Times has followed up on last week's Bloomberg report of OpenAI courting investment partners in the Middle East. FT's news piece alleges that Altman is in talks with billionaire businessman Sheikh Tahnoon bin Zayed al-Nahyan, a very well connected member of the United Arab Emirates Royal Family. OpenAI's leadership is reportedly negotiating with TSMC—The Financial Times alleges that Taiwan's top chip foundry is an ideal manufacturing partner. This revelation contradicts Bloomberg's recent reports of a potential custom OpenAI AI chip venture involving purpose-built manufacturing facilities. The whole project is said to be at an early stage of development, so Altman and his colleagues are most likely exploring a variety of options.

The Federal Trade Commission announced today that it issued orders to five companies requiring them to provide information regarding recent investments and partnerships involving generative AI companies and major cloud service providers. The agency's 6(b) inquiry will scrutinize corporate partnerships and investments with AI providers to build a better internal understanding of these relationships and their impact on the competitive landscape. The compulsory orders were sent to Alphabet, Inc., Amazon.com, Inc., Anthropic PBC, Microsoft Corp., and OpenAI, Inc.

"History shows that new technologies can create new markets and healthy competition. As companies race to develop and monetize AI, we must guard against tactics that foreclose this opportunity, "said FTC Chair Lina M. Khan. "Our study will shed light on whether investments and partnerships pursued by dominant companies risk distorting innovation and undermining fair competition."

OpenAI CEO, Sam Altman, had a turbulent winter 2023 career moment, but appears to be going all in with his company's future interests. A Bloomberg report suggests that the tech visionary has initiated a major fundraising initiative for the construction of OpenAI-specific semiconductor production plants. The AI evangelist reckons that his industry will become prevalent enough to demand a dedicated network of manufacturing facilities—the U.S. based artificial intelligence (AI) research organization is (reportedly) exploring custom artificial intelligence chip designs. Proprietary AI-focused GPUs and accelerators are not novelties at this stage in time—many top tech companies rely on NVIDIA solutions, but are keen to deploy custom-built hardware in the near future.

OpenAI's popular ChatGPT system is reliant on NVIDIA H100 and A100 GPUs, but tailor-made alternatives seem to be the desired route for Altman & Co. The "on their own terms" pathway seemingly skips an expected/traditional chip manufacturing process—the big foundries could struggle to keep up with demand for AI-oriented silicon. G42 (an Abu Dhabi-based AI development holding company) and SoftBank Group are mentioned as prime investment partners in OpenAI's fledgling scheme—Bloomberg proposes that Altman's team is negotiating a $8 to 10 billion deal with top brass at G42. OpenAI's planned creation of its own foundry network is certainly a lofty and costly goal—the report does not specify whether existing facilities will be purchased and overhauled, or new plants being constructed entirely from scratch.

Today, Microsoft launched Copilot Pro, bringing its AI-powered productivity features to mainstream consumers. Available as a $20 per month add-on to Microsoft 365 Personal or Home subscriptions, Copilot Pro injects AI directly into Office apps to help users write faster and work smarter. The key features include AI-generated text suggestions and summaries in Word, automated data analysis and graph creation in Excel, and even entire PowerPoint presentation generation from a text prompt. Copilot can also suggest email replies in Outlook and assist with other productivity tasks. What sets Copilot Pro apart from the free Copilot assistant is its tight integration with Office apps and ability to summarize long Word documents and generate entire decks. The Pro version also offers priority access to the latest AI models from OpenAI, Microsoft's key partner. The regular Copilot uses GPT-4 during non-priority times, while the Copilot Pro aims to serve its users with GPT-4 and GPT-4 Turbo all the time.

While regular Copilot is available to anyone with a Microsoft account, Copilot Pro is reserved for those with active Microsoft 365 subscriptions. However, it brings previously business-only AI capabilities like PowerPoint generation to mainstream users. Microsoft's Divya Kumar, global head of marketing for search and AI at Microsoft, stated in a discussion for The Verge that Copilot Pro will continue to expand over time: "Given that pattern we've been in, that rolling thunder, you can expect we're going to do the exact same thing for Copilot Pro." So, while the initial launch focuses on core Office apps, expect Copilot Pro to pop up across Microsoft's software and services eventually. For now, it aims to boost productivity for Office power users willing to pay a little extra for AI assistance.

Today at the "Advancing AI" event, AMD was joined by industry leaders including Microsoft, Meta, Oracle, Dell Technologies, HPE, Lenovo, Supermicro, Arista, Broadcom and Cisco to showcase how these companies are working with AMD to deliver advanced AI solutions spanning from cloud to enterprise and PCs. AMD launched multiple new products at the event, including the AMD Instinct MI300 Series data center AI accelerators, ROCm 6 open software stack with significant optimizations and new features supporting Large Language Models (LLMs) and Ryzen 8040 Series processors with Ryzen AI.

"AI is the future of computing and AMD is uniquely positioned to power the end-to-end infrastructure that will define this AI era, from massive cloud installations to enterprise clusters and AI-enabled intelligent embedded devices and PCs," said AMD Chair and CEO Dr. Lisa Su. "We are seeing very strong demand for our new Instinct MI300 GPUs, which are the highest-performance accelerators in the world for generative AI. We are also building significant momentum for our data center AI solutions with the largest cloud companies, the industry's top server providers, and the most innovative AI startups ꟷ who we are working closely with to rapidly bring Instinct MI300 solutions to market that will dramatically accelerate the pace of innovation across the entire AI ecosystem."

Over the past few days, the OpenAI drama has continued to give more details about the relationship between OpenAI's board, employees, and even the executive layer of the company. As we have covered previously, the OpenAI board on last Friday, November 17, fired the company's CEO, Sam Altman. Over the weekend, Mr. Altman was approached by Microsoft CEO Satya Nadella and offered to lead the AI unit within the Redmond giant; however, the employment was not yet finalized. Today, we learned that Sam Altman has reached an agreement with the board to return to OpenAI along with Greg Brockman and many other OpenAI employees.

After starting a wave of posts on the X/Twitter platform saying, "OpenAI is nothing without its people," the employees of OpenAI signed a letter requesting the board to bring back Sam Altman. With the deal now happening, employees are expected to continue working for OpenAI under Sam Altman's leadership. The new initial board of OpenAI is composed of Bret Taylor (Chair), Larry Summers, and Adam D'Angelo. Sam Altman said in a post on X: "i love openai, and everything i've done over the past few days has been in service of keeping this team and its mission together. when i decided to join msft on sun evening, it was clear that was the best path for me and the team. with the new board and w satya's support, i'm looking forward to returning to openai, and building on our strong partnership with msft." While Microsoft CEO Satya Nadella added "We are encouraged by the changes to the OpenAI board. We believe this is a first essential step on a path to more stable, well-informed, and effective governance. Sam, Greg, and I have talked and agreed they have a key role to play along with the OAI leadership team in ensuring OAI continues to thrive and build on its mission. We look forward to building on our strong partnership and delivering the value of this next generation of AI to our customers and partners."

On Friday, the AI world was caught by storm as the board of directors of OpenAI, the maker of ChatGPT and other AI software, fired its CEO, Sam Altman. According to multiple sources reporting the state of OpenAI, Sam Altman was stunned by the board's decision of his removal, where the company published a public statement with many remarks, primarily informing the public that "Mr. Altman's departure follows a deliberative review process by the board, which concluded that he was not consistently candid in his communications with the board, hindering its ability to exercise its responsibilities. The board no longer has confidence in his ability to continue leading OpenAI."

After Sam Altman's leave, Greg Brockman, president and co-founder of OpenAI, announced that he was also leaving the company. Satya Nadella, CEO of Microsoft, and other investors have stepped in to lead negotiations between the OpenAI board and Sam Altman to return to his position as the CEO of the non-profit company. However, according to The Information, Sam Altman will not be returning as the CEO, and instead, Emmett Shear will be appointed as the interim CEO of OpenAI. It is also reported that the departure of Sam Altman is now being followed by three senior researchers, Jakub Pachocki, Aleksander Madry, and Szymon Sidor, who have left the company to follow Sam Altman's next adventure. They wanted to go back to OpenAI if Mr. Altman would return; however, with Emmett Shear now being appointed as interim CEO, the company is in shambles with its senior staff employment in question.Update 15:30 UTC: Sam Altman has joined Microsoft alongside Greg Brockman to lead Microsoft's advanced AI research efforts; additionally with hundreds of OpenAI staff wanting to do projects under Sam Altman's lead. Apparently there are 700 members of staff, and 505 of them plan to follow Mr. Altman and Mr. Brockman under Microsoft's wing.

During its Ignite conference, Microsoft introduced a duo of custom-designed silicon made to accelerate AI and excel in cloud workloads. First of the two is Microsoft's Azure Cobalt 100 CPU, a 128-core design that features a 64-bit Armv9 instruction set, implemented in a cloud-native design that is set to become a part of Microsoft's offerings. While there aren't many details regarding the configuration, the company claims that the performance target is up to 40% when compared to the current generation of Arm servers running on Azure cloud. The SoC has used Arm's Neoverse CSS platform customized for Microsoft, with presumably Arm Neoverse N2 cores.

The next and hottest topic in the server space is AI acceleration, which is needed for running today's large language models. Microsoft hosts OpenAI's ChatGPT, Microsoft's Copilot, and many other AI services. To help make them run as fast as possible, Microsoft's project Athena now has the name of Maia 100 AI accelerator, which is manufactured on TSMC's 5 nm process. It features 105 billion transistors and supports various MX data formats, even those smaller than 8-bit bit, for maximum performance. Currently tested on GPT 3.5 Turbo, we have yet to see performance figures and comparisons with competing hardware from NVIDIA, like H100/H200 and AMD, with MI300X. The Maia 100 has an aggregate bandwidth of 4.8 Terabits per accelerator, which uses a custom Ethernet-based networking protocol for scaling. These chips are expected to appear in Microsoft data centers early next year, and we hope to get some performance numbers soon.

Even as CPU vendors are working to mainstream accelerated AI for client PCs, and Microsoft setting the pace for more AI in everyday applications with Windows 11 23H2 Update; NVIDIA is out there reminding you that every GeForce RTX GPU is an AI accelerator. This is thanks to its Tensor cores, and the SIMD muscle of the ubiquitous CUDA cores. NVIDIA has been making these for over 5 years now, and has an install base of over 100 million. The company is hence focusing on bring generative AI acceleration to more client- and enthusiast relevant use-cases, such as large language models.

NVIDIA at the Microsoft Ignite event announced new optimizations, models, and resources to bring accelerated AI to everyone with an NVIDIA GPU that meets the hardware requirements. To begin with, the company introduced an update to TensorRT-LLM for Windows, a library that leverages NVIDIA RTX architecture for accelerating large language models (LLMs). The new TensorRT-LLM version 0.6.0 will release later this month, and improve LLM inference performance by up to 5 times in terms of tokens per second, when compared to the initial release of TensorRT-LLM from October 2023. In addition, TensorRT-LLM 0.6.0 will introduce support for popular LLMs, including Mistral 7B and Nemtron-3 8B. Accelerating these two will require a GeForce RTX 30-series "Ampere" or 40-series "Ada" GPU with at least 8 GB of main memory.

OpenAI, the company behind ChatGPT and the GPT-4 large language model, is reportedly exploring the possibility of creating custom silicon to power its next-generation AI models. According to Reuters, Insider sources have even alluded to the firm evaluating potential acquisitions of chip design firms. While a final decision is yet to be cemented, conversations from as early as last year highlighted OpenAI's struggle with the growing scarcity and escalating costs of AI chips, with NVIDIA being its primary supplier. The CEO of OpenAI, Sam Altman, has been rather vocal about the shortage of GPUs, a sector predominantly monopolized by NVIDIA, which holds control over an astounding 80% of the global market for AI-optimized chips.

Back in 2020, OpenAI banked on a colossal supercomputer crafted by Microsoft, a significant investor in OpenAI, which harnesses the power of 10,000 NVIDIA GPUs. This setup is instrumental in driving the operations of ChatGPT, which, as per Bernstein's analyst Stacy Rasgon, comes with its own hefty price tag. Each interaction with ChatGPT is estimated to cost around 4 cents. Drawing a comparative scale with Google search, if ChatGPT queries ever burgeoned to a mere tenth of Google's search volume, the initial GPU investment would skyrocket to an overwhelming $48.1 billion, with a recurring annual expenditure of approximately $16 billion for sustained operations. For an invitation to comment, OpenAI declined to provide any statements. The potential entry into the world of custom silicon signals a strategic move towards greater self-reliance and cost optimization so further development of AI can be sustained.

Generative AI is no longer just for tech giants. With GeForce, it's already at your fingertips. Gone are the days when AI was the domain of sprawling data centers or elite researchers. For GeForce RTX users, AI is now running on your PC. It's personal, enhancing every keystroke, every frame and every moment. Gamers are already enjoying the benefits of AI in over 300 RTX games. Meanwhile, content creators have access to over 100 RTX creative and design apps, with AI enhancing everything from video and photo editing to asset generation. And for GeForce enthusiasts, it's just the beginning. RTX is the platform for today and the accelerator that will power the AI of tomorrow.

How Did AI and Gaming Converge?
NVIDIA pioneered the integration of AI and gaming with DLSS, a technique that uses AI to generate pixels in video games automatically and which has increased frame rates by up to 4x. And with the recent introduction of DLSS 3.5, NVIDIA has enhanced the visual quality in some of the world's top titles, setting a new standard for visually richer and more immersive gameplay. But NVIDIA's AI integration doesn't stop there. Tools like RTX Remix empower game modders to remaster classic content using high-quality textures and materials generated by AI.

When OpenAI announced its GPT-4 model, it first became a part of ChatGPT, behind the paywall for premium users. The GPT-4 is the latest installment in the Generative Pretrained Transformer (GPT) Large Language Models (LLMs). The GPT-4 aims to be a more capable version than the GPT-3.5 that powered ChatGPT at first, which was capable once it launched. However, it seems like the performance of GPT-4 has been steadily dropping since its introduction. Many users noted the regression, and today we have researchers from Stanford University and UC Berkeley, who benchmarked the GPT-4 performance in March 2023, and the model's performance in June 2023 in tasks like solving math problems, visual reasoning, code generation, and answering sensitive questions.

The results? The paper shows that GPT-4 performance has been significantly degraded in all the tasks. This could be attributed to improving stability, lowering the massive compute demand, and much more. What is unexpected, GPT-3.5 experienced a significant uplift in the same period. Below, you can see the examples that were benchmarked by the researchers, which also compare GTP-4 and GPT-3.5 performance in all cases.

A watershed moment on Nov. 22, 2022, was mostly virtual, yet it shook the foundations of nearly every industry on the planet. On that day, OpenAI released ChatGPT, the most advanced artificial intelligence chatbot ever developed. This set off demand for generative AI applications that help businesses become more efficient, from providing consumers with answers to their questions to accelerating the work of researchers as they seek scientific breakthroughs, and much, much more.

Businesses that previously dabbled in AI are now rushing to adopt and deploy the latest applications. Generative AI—the ability of algorithms to create new text, images, sounds, animations, 3D models and even computer code—is moving at warp speed, transforming the way people work and play. By employing large language models (LLMs) to handle queries, the technology can dramatically reduce the time people devote to manual tasks like searching for and compiling information.

OpenAI's CEO, Sam Altman, is currently exploring the UK and Europe on a PR-related "mini" world tour, and protesters have been following these proceedings with much interest. UK news outlets have reported that a demonstration took place outside of a university building in London yesterday, where the UCL Events organization hosted Altman as part of a fireside discussion about the benefits and problems relating to advanced AI systems. Attendees noted that Altman expressed optimism about AI's potential for the creation of more jobs and reduction in inequality - despite calls for a major pause on development. He also visited 10 Downing Street during the British leg of his PR journey - alongside other AI company leaders - to talk about potential risks (originating from his industry) with the UK's prime minister. Discussed topics were reported to include national security, existential threats and disinformation.

At the UCL event, Altman touched upon his recent meetings with European regulators, who are developing plans for advanced legislation that could lead to targeted laws (applicable to AI industries). He says that his company is "gonna try to comply" with these potential new rules and agrees that some form of regulation is necessary: "something between the traditional European approach and the traditional US approach" would be preferred. He took issue with the potential branding of large AI models (such as OpenAI's ChatGPT and GPT-4 applications) as "high risk" ventures via the European Union's AI Act provisions: "Either we'll be able to solve those requirements or not...If we can comply, we will, and if we can't, we'll cease operating… We will try. But there are technical limits to what's possible."

Geoffrey Hinton, British-Canadian psychologist, computer scientist, and 2018 Turing Award winner in deep learning, has departed the Google Brain team after a decade-long tenure. His research on AI and neural networks dating back to the 1980s has helped shape the current landscape of deep learning, neural processing, and artificial intelligence algorithms with direct and indirect contributions over the years. 2012's AlexNet, designed and developed in collaboration with his students Alex Krizhevsky and Ilya Sutskever, formed the modern backbone of computer vision and AI image recognition used today in Generative AI. Hinton joined Google when the company won the bid for the tiny startup he and his two students formed in the months following the reveal of AlexNet. Ilya Sutskever left their cohort at Google in 2015 to become co-founder and Chief Scientist of OpenAI; creators of ChatGPT and one of Google's most prominent competitors.

In an interview with the New York Times Hinton says that he quit his position at Google so that he may speak freely about the risks of AI, and that a part of him regrets his life's work in the field. He said that during his time there Google has acted as a "proper steward" of AI development, and was careful about releasing anything that might be harmful. His viewpoint on the industry shifted within the last year as Microsoft's Bing Chat took shots at Google's core business, the web browser, leading to Google being more reactionary than deliberate in response with Bard. The concern arises that as these companies battle it out for AI supremacy they won't take proper precautions against bad-faith actors using the technologies to flood the internet with false photos, text, and even videos. That the average person would no longer be able to tell what was real, and what was manufactured by AI prompt.

Alphabet Incorporated's Google AI division has today revealed a planned update for its Bard conversational artificial intelligence chatbot. The experimental generative artificial intelligence software application will become capable of assisting people in the writing of computer code - the American multinational technology company hopes that Bard will be of great to help in the area of software development. Paige Bailey, a group product manager at Google Research has introduced the upcoming changes: "Since we launched Bard, our experiment that lets you collaborate with generative AI, coding has been one of the top requests we've received from our users. As a product lead in Google Research - and a passionate engineer who still programs every day - I'm excited that today we're updating Bard to include that capability."

The Bard chatbot was made available, on a trial basis, to users in the USA and UK last month. Google's AI team is reported to be under great pressure to advance the Bard chatbot into a suitably powerful state in order to compete with its closest rival - Microsoft Corporation. The Seattle-based giant has invested heavily into Open AI's industry leading ChatGPT application. Google's latest volley against its rivals shows that Bard's has become very sophisticated - so much so that the app is able to chew through a variety of programming languages. Bailey outlines these features in the company's latest blog: "Starting now, Bard can help with programming and software development tasks, including code generation, debugging and code explanation. We're launching these capabilities in more than 20 programming languages including C++, Go, Java, Javascript, Python and Typescript. And you can easily export Python code to Google Colab - no copy and paste required." Critics of AI-driven large language models have posited that the technology could potentially eliminate humans from the job market - it will be interesting to observe the coder community's reaction to Google marketing of Bard as a helpful tool in software development.

Giga Computing, a subsidiary of GIGABYTE and an industry leader in high-performance servers, server motherboards, and workstations, today announced a lineup of powerful GPU-centric servers with the latest AMD and Intel CPUs, including NVIDIA HGX H100 servers with both 4-GPU and 8-GPU modules. With growing interest in HPC and AI applications, specifically generative AI (GAI), this breed of server relies heavily on GPU resources to tackle compute-heavy workloads that handle large amounts of data. With the advent of OpenAI's ChatGPT and other AI chatbots, large GPU clusters are being deployed with system-level optimization to train large language models (LLMs). These LLMs can be processed by GIGABYTE's new design-optimized systems that offer a high level of customization based on users' workloads and requirements.

The GIGABYTE G-series servers are built first and foremost to support dense GPU compute and the latest PCIe technology. Starting with the 2U servers, the new G293 servers can support up to 8 dual-slot GPUs or 16 single-slot GPUs, depending on the server model. For the ultimate in CPU and GPU performance, the 4U G493 servers offer plenty of networking options and storage configurations to go alongside support for eight (Gen 5 x16) GPUs. And for the highest level of GPU compute for HPC and AI, the G393 & G593 series support NVIDIA H100 Tensor Core GPUs. All these new two CPU socket servers are designed for either 4th Gen AMD EPYC processors or 4th Gen Intel Xeon Scalable processors.

According to The Information, Microsoft has been working on creating custom processors for processing AI with a project codenamed Athena. Based on TSMC's 5 nm process, these chips are designed to accelerate AI workloads and scale to hundreds or even thousands of chips. With the boom of Large Language Models (LLMs) that require billions of parameters, training them requires a rapid increase of computational power to a point where companies purchase hundreds of thousands of GPUs from the likes of NVIDIA. However, creating custom processors is a familiar feat for a company like Microsoft. Hyperscalers like AWS, Google, and Meta are already invested in the creation of processors for AI training, and Microsoft is just joining as well.

While we don't have much information about these processors, we know that Microsoft started the project in 2019, and today these processors are in the hands of select employees of Microsoft and OpenAI that work with AI projects and need computational horsepower. Interestingly, some projections assume that if Microsoft could match NVIDIA's GPU performance, the cost would only be a third of NVIDIA's offerings. However, it is challenging to predict that until more information is provided. Microsoft plans to make these chips more widely available as early as next year; however, there is no specific information on when and how, but Azure cloud customers would be the most logical place to start.

According to Business Insider, Twitter has made a substantial investment into hardware upgrades at its North American datacenter operation. The company has purchased somewhere in the region of 10,000 GPUs - destined for the social media giant's two remaining datacenter locations. Insider sources claim that Elon Musk has committed to a large language model (LLM) project, in an effort to rival OpenAI's ChatGPT system. The GPUs will not provide much computational value in the current/normal day-to-day tasks at Twitter - the source reckons that the extra processing power will be utilized for deep learning purposes.

Twitter has not revealed any concrete plans for its relatively new in-house artificial intelligence project but something was afoot when, earlier this year, Musk recruited several research personnel from Alphabet's DeepMind division. It was theorized that he was incubating a resident AI research lab at the time, following personal criticisms levelled at his former colleagues at OpenAI, ergo their very popular and much adopted chatbot.

Last Tuesday, Alibaba announced its intentions to put out its own artificial intelligence (AI) chatbot product called Tongyi Qianwen - another rival to take on OpenAI's pioneering ChatGPT natural language processing tool. The Chinese technology giant is hoping to retrofit the new chatbot system into several arms of its business operations. Alibaba had revealed initial plans for chatbot integration earlier this year, and mentioned that it was providing an alternative to the already well established ChatGPT tool. Alibaba's workplace messaging application - DingTalk - is slated to receive the first AI-powered update in the near future, although the company did not provide a firm timeline for Tongyi Qianwen's release window.

The product name "Tongyi Qianwen" loosely translates to "seeking an answer by asking a thousand questions" - Alibaba did not provide an official English language translation at last week's press conference. Their chatbot is reported to function in both Mandarin and English language modes. Advanced AI voice recognition is set for usage in the Tmall Genie range of smart speakers (similar in function to the Amazon Echo). Alibaba expects to expand Tongyi Qianwen's reach into applications relating to e-commerce and mapping services.

Microsoft Corp. on Tuesday announced it is bringing the next generation of AI to cybersecurity with the launch of Microsoft Security Copilot, giving defenders a much-needed tool to quickly detect and respond to threats and better understand the threat landscape overall. Security Copilot will combine Microsoft's vast threat intelligence footprint with industry-leading expertise to augment the work of security professionals through an easy-to-use AI assistant.

"Today the odds remain stacked against cybersecurity professionals. Too often, they fight an asymmetric battle against relentless and sophisticated attackers," said Vasu Jakkal, corporate vice president, Microsoft Security. "With Security Copilot, we are shifting the balance of power into our favor. Security Copilot is the first and only generative AI security product enabling defenders to move at the speed and scale of AI."

Newegg Commerce, Inc., a leading global technology e-commerce retailer, announced today that the company is using ChatGPT to improve its customers' online shopping experience. Introduced in November 2022, ChatGPT from OpenAI is a conversational artificial intelligence (AI) program capable of providing information that improves efficiency in myriad situations.

"We're always evaluating our e-commerce technology to ensure we're providing the best customer experience. Through testing, we've proven that ChatGPT has a practical use for Newegg based on the added quality and efficiency it creates," said Lucy Huo, Vice President of Application Development for Newegg. "We deployed ChatGPT to improve content both on-site and off-site to help customers find what they want and elevate their experience. AI doesn't replace employees, but it adds resources so employees are available to handle more complex projects. We're still in the early phases of AI but the benefits for e-commerce may be substantial."

NVIDIA and key partners today announced the availability of new products and services featuring the NVIDIA H100 Tensor Core GPU—the world's most powerful GPU for AI—to address rapidly growing demand for generative AI training and inference. Oracle Cloud Infrastructure (OCI) announced the limited availability of new OCI Compute bare-metal GPU instances featuring H100 GPUs. Additionally, Amazon Web Services announced its forthcoming EC2 UltraClusters of Amazon EC2 P5 instances, which can scale in size up to 20,000 interconnected H100 GPUs. This follows Microsoft Azure's private preview announcement last week for its H100 virtual machine, ND H100 v5.

Additionally, Meta has now deployed its H100-powered Grand Teton AI supercomputer internally for its AI production and research teams. NVIDIA founder and CEO Jensen Huang announced during his GTC keynote today that NVIDIA DGX H100 AI supercomputers are in full production and will be coming soon to enterprises worldwide.

We're starting to open access to Bard, an early experiment that lets you collaborate with generative AI. We're beginning with the U.S. and the U.K., and will expand to more countries and languages over time. Today we're starting to open access to Bard, an early experiment that lets you collaborate with generative AI. This follows our announcements from last week as we continue to bring helpful AI experiences to people, businesses and communities.

You can use Bard to boost your productivity, accelerate your ideas and fuel your curiosity. You might ask Bard to give you tips to reach your goal of reading more books this year, explain quantum physics in simple terms or spark your creativity by outlining a blog post. We've learned a lot so far by testing Bard, and the next critical step in improving it is to get feedback from more people.