The world of AI has already had a busy start to 2024: the past week has seen acquisitions, partnerships, launches and much more. Let’s cut through the noise by highlighting five of the week’s top AI news headlines.
Google launches Gemini Ultra
Last December, Google announced Gemini, its most advanced model to date. The multimodal Gemini model powers the Bard chatbot, can handle complex, domain-specific questions, and delivers significantly improved speed and accuracy for coding tasks.
Google has made it clear that Gemini is more than just a model: it represents a mindset shift. Gemini supports the foundation of an entire Google AI ecosystem, from products and assistants targeting end users to APIs and platforms for builders and developers.
As of December, only the Pro tier of Gemini was available through Bard. Although it was more sophisticated than Google’s other models, its performance was about on par with OpenAI’s GPT-3.5. But last week, Google revealed its Ultra model to users via a new AI assistant called Gemini Advanced. Google said that Gemini can outperform human experts in massive multitasking language comprehension, a method that uses a combination of 57 subjects – including mathematics, physics, history, law, medicine and ethics – to test knowledge and problem-solving skills.
The other 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 its AI practice with the acquisition of OpTeamizer
TechTarget Corporate Strategy Group (ESG) Research showed that the main challenge organizations face today when it comes to implementing generative AI is the lack of employee expertise and skills. In light of this skills gap, the next natural question is where organizations turn for help – and ESG research watch that the answer lies in management consulting.
On February 5, Deloitte announced its acquisition from OpTeamizer, which specializes in creating and implementing AI running on Nvidia-accelerated hardware. This is great news for Deloitte clients, who already see value in Deloitte’s existing alliance with Nvidia. OpTeamizer’s AI and data science experts have extensive experience in Nvidia technology, ranging from training workshops to high-performance computing and Nvidia’s CUDA software framework, to name a few.
This acquisition represents a huge opportunity for Deloitte to expand its generative AI portfolio, capabilities and presence across the entire AI stack. Additionally, this highlights Deloitte’s commitment to its customer-focused 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 a expansion of their partnership that extends to the data center, with integrated data center offerings. This collaboration includes the integration of Nvidia’s Tensor Core GPUs into Cisco’s M7 UCS rack and blade servers, jointly validated reference architectures, and support for Cisco Networking Cloud. It also encompasses digital experience monitoring using ThousandEyes, Cisco Observability Platform and more.
Suppliers are increasingly offering comprehensive offerings with their partner ecosystems, and this announcement continues the trend of simplification and faster time to value. Reference architectures, in particular, highlight this, combining the capabilities of Cisco and Nvidia with partners such as Pure Storage, NetApp and Red Hat to simplify the deployment of AI infrastructure.
What might be overlooked in this announcement is on the network side. Obviously, Cisco is a leader in the networking space, but the most interesting aspect here is Nvidia’s involvement, given the company’s interest in InfiniBand to support AI. Although Nvidia will continue to promote InfiniBand, this announcement highlights Nvidia’s recognition of the need to support customers’ network preferences.
Hugging Face to challenge OpenAI on the AI assistant front
I would say the simplest and most natural use case for generative AI today is simply using an AI assistant, which can streamline operations, improve efficiency, and improve productivity. The value proposition of these assistants lies in their ability to automate routine tasks, reduce errors, and process information relentlessly.
While there are several enterprise generative AI assistants on the market, including Microsoft’s Copilot, Google’s Duet AI, and AWS’ Amazon Q, organizations continue to explore ways to create their own.
OpenAI’s custom GPT generator has enabled this feature, but it requires a paid subscription and only works with OpenAI’s proprietary LLM, ChatGPT. Many organizations want to build similar functionality using their favorite open source models.
Hugging Face has made this possible with the launch of third-party, customizable Hugging Chat Assistants, Hugging Face’s alternative to OpenAI’s GPTs. announcement February 2. With Hugging Chat Assistants, users can create personalized versions of Hugging Face Chat in just two clicks. Plus, they can do it for free, using whatever open source LLM they want to power the AI assistant.
IBM announces new AI Alliance members and working groups
There is a very strong ecosystem of vendors, partners, and consultants driving the adoption of trusted AI. This is one of the main reasons why IBM, Meta and many support providers created the AI Alliance, a group of leading technology providers, startups, academics and others who see the value of an open, collaborative ecosystem and are committed to helping further those same goals. The goal of the alliance is to accelerate and spread open innovation across the AI technology landscape to improve fundamental capabilities, safety, security and trust in AI, and to maximize responsibly benefits people and society around the world.
I was disappointed to see some major vendors missing from the membership list, including Google, Microsoft, AWS, Nvidia, and OpenAI. The good news is that new members continue to come in – and even though there’s no one on the aforementioned list, there are still some really big names in tech, including Databricks, Snowflake, and Uber.
In my opinion, the most important element of this announcement concerns the two new working groups: the AI Safety and Trust Tooling 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 everything from outlining best practices for AI safety, trust, ethics, and cybersecurity, to establishing a definitive set of benchmarking capabilities, to to public sharing of information on key policy topics, including red teaming, app regulation, and access to hardware.
Mike Leone is a principal analyst in TechTarget’s business strategy group, where he covers data, analytics and AI.
Enterprise Strategy Group is a division of TechTarget. Its analysts maintain business relationships with technology providers.
