The world of AI is already off to a busy start to 2024, with acquisitions, partnerships, and releases taking place over the last week. Cut through the noise with five of this week's top AI news headlines.
Google releases Gemini Ultra
Back in December, Google announced its most advanced model to date, Gemini. The multimodal Gemini model powers the Bard chatbot to handle complex, domain-specific questions, significantly increasing the speed and accuracy of coding tasks.
Google has made it clear that Gemini is more than just a model, it represents a change in thinking. Gemini supports the foundation of the entire Google AI ecosystem, from products and assistants for end users to APIs and platforms for builders and developers.
Back in December, only the Pro level of Gemini was available from Bard. Although more sophisticated than other Google models, its performance was about the same as OpenAI's GPT-3.5. But last week, Google released an Ultra model to users through a new AI assistant called Gemini Advanced. According to Google, Gemini is a way to test knowledge and problem-solving skills by combining 57 subjects including mathematics, physics, history, law, medicine, and ethics. It is said that they are able to outperform experts.
Another difference between Gemini Pro and Gemini Advanced, which uses the Ultra version of the model, is cost. Gemini Advanced requires a subscription to the new Google One AI premium plan.
Deloitte strengthens AI practice with acquisition of OpTeamizer
A study by TechTarget's Enterprise Strategy Group (ESG) found that the biggest challenge facing organizations today when it comes to implementing generative AI is a lack of employee expertise and skills. Given this skills gap, the natural next question is where are organizations looking for help? ESG research shows that the answer is management consultants.
On February 5, Deloitte announced the acquisition of OpTeamizer, which specializes in building and implementing AI running on Nvidia accelerated computing hardware. This is great news for Deloitte customers who already see value in Deloitte and his existing partnership with Nvidia. OpTeamizer's AI and data science experts have extensive experience with Nvidia technologies, including everything from training his workshops to his High Performance Computing and Nvidia's CUDA software frameworks. have.
This acquisition presents a significant opportunity for Deloitte to expand its portfolio, capabilities and generative AI presence across the AI stack. Additionally, he highlights Deloitte's commitment to customer-facing generative AI initiatives.
Cisco and Nvidia expand partnership on AI deployment and management
At the Cisco Live conference in Amsterdam on February 6, Cisco and Nvidia announced that they are extending their partnership into the data center with integrated data center products. The collaboration includes the integration of Nvidia's Tensor Core GPUs into Cisco M7 UCS rack and blade servers, a jointly validated reference architecture, and support for the Cisco Networking Cloud. It also includes monitoring digital experiences using ThousandEyes, Cisco Observability Platform, and more.
Vendors are increasingly combining partner ecosystems with full-stack products, and this announcement continues the trend of simplifying and accelerating time to value. The reference architecture specifically emphasizes this, combining Cisco and his Nvidia capabilities with partners such as Pure Storage, NetApp, and Red Hat to take the guesswork out of deploying AI infrastructure.
What might be overlooked in this announcement is the networking side. Cisco is clearly the leader in networking, but what's more interesting here is Nvidia's involvement, given the company's interest in his InfiniBand, which supports his AI. . While Nvidia continues to promote InfiniBand, this announcement emphasizes that Nvidia recognizes the need to support customers' networking configurations.
Face-hugging to take on OpenAI in terms of AI assistants
I would argue that the simplest and most natural generative AI use case today is simply using an AI assistant. This allows you to streamline operations, increase efficiency, and improve productivity. The value proposition of these assistants is their ability to automate routine tasks, reduce errors, and process information energetically.
While there are several enterprise-generated AI assistants on the market, including Microsoft's Copilot, Google's Duet AI, and AWS' Amazon Q, organizations continue to explore ways to build their own AI assistants.
OpenAI's custom GPT builder enabled this feature, but it requires a paid subscription and only works with OpenAI's own LLM, ChatGPT. Many organizations want to build similar functionality using their preferred open source model.
Hugging Face has made this possible through the release of Hugging Face's third-party customizable Hugging Chat Assistant, which replaces OpenAI's GPT. announced Hug Chat Assistant allows users to create a custom version of Hug Face Chat in just two clicks. Additionally, you can run it for free with the open source LLM that powers the AI assistant at your disposal.
IBM announces new AI Alliance members and working groups
There is a robust ecosystem of vendors, partners, and consultancies that are driving the adoption of trusted AI. This is why IBM, Meta, and many supporting vendors understand the value of an open, collaborative ecosystem and are a group of leading technology vendors, startups, academics, and others committed to helping advance the same goals. This is a big reason why we founded the AI Alliance. The Alliance's focus is to accelerate and disseminate open innovation across the field of AI technology, improve AI's fundamental capabilities, safety, security, and reliability, and responsibly deliver benefits to people and societies everywhere. It's about having and maximizing it.
We were disappointed to see several major vendors dropped from our membership list, including Google, Microsoft, AWS, Nvidia, and OpenAI. The good news is that new members continue to join. Although no one is on the aforementioned list, there are still some very well-known companies in the technology industry, such as Databricks, Snowflake, and Uber.
In my view, the biggest component of this announcement is two new working groups: the AI Safety and Trust Tools Group and the AI Policy Advocacy Working Group. The goal of these groups is to bring together leading researchers, developers, policymakers, and industry experts to address the challenges of generative AI and democratize its benefits. This includes an overview of best practices for AI safety, trust, ethics, and cybersecurity, to establishing a definitive set of benchmarking capabilities, and key policies such as red teaming, application regulation, and access to hardware. This includes everything from publicly sharing information about a topic.
Mike Leone is a Principal Analyst in TechTarget's Enterprise Strategy Group, covering data, analytics, and AI.
Enterprise Strategy Group is a division of TechTarget. The company's analysts have business relationships with technology vendors.
