Google I/O wrap-up: Gemini AI updates, new search features and more
Google CEO Sundar Pichai speaks at the Google I/O developer conference.
Andrej Sokolow | Picture Alliance | Getty Images
Google on Tuesday hosted its annual I/O developer conference, and rolled out a range of artificial intelligence products, from new search and chat features to AI hardware for cloud customers. The announcements underscore the company’s focus on AI as it fends off competitors, such as OpenAI.
Many of the features or tools Google unveiled are only in a testing phase or limited to developers, but they give an idea of how the tech giant is thinking about AI and where it’s investing. Google makes money from AI by charging developers who use its models and from customers who pay for Gemini Advanced, its competitor to ChatGPT, which costs $19.99 per month and can help users summarize PDFs, Google Docs and more.
Tuesday’s announcements follow similar events held by its AI competitors. Earlier this month, Amazon-backed Anthropic announced its first-ever enterprise offering and a free iPhone app. Meanwhile, OpenAI on Monday launched a new AI model and desktop version of ChatGPT, along with a new user interface.
Here’s what Google announced.
Gemini AI updates
Google introduced updates to Gemini 1.5 Pro, its AI model that will soon be able to handle even more data — for example, the tool can summarize 1,500 pages of text uploaded by a user.
There’s also a new Gemini 1.5 Flash AI model, which the company said is more cost-effective and designed for smaller tasks like quickly summarizing conversations, captioning images and videos and pulling data from large documents.
Google CEO Sundar Pichai highlighted improvements to Gemini’s translations, adding that it will be available to all developers worldwide in 35 languages. Within Gmail, Gemini 1.5 Pro will analyze attached PDFs and videos, giving summaries and more, Pichai said. That means that if you missed a long email thread on vacation, Gemini will be able to summarize it along with any attachments.
The new Gemini updates are also helpful for searching Gmail. One example the company gave: If you’ve been comparing prices from different contractors to fix your roof and are looking for a summary to help you decide who to pick, Gemini could return three quotes along with the anticipated start dates offered in the different email threads.
Google said Gemini will eventually replace Google Assistant on Android phones, suggesting it’s going to be a more powerful competitor to Apple’s Siri on iPhone.
Google Veo, Imagen 3 and Audio Overviews
Google announced “Veo,” its latest model for generating high-definition video, and Imagen 3, its highest quality text-to-image model, which promises lifelike images and “fewer distracting visual artifacts than our prior models.”
The tools will be available for select creators on Monday and will come to Vertex AI, Google’s machine learning platform that lets developers train and deploy AI applications.
The company also showcased “Audio Overviews,” the ability to generate audio discussions based on text input. For instance, if a user uploads a lesson plan, the chatbot can speak a summary of it. Or, if you ask for an example of a science problem in real life, it can do so through interactive audio.
Separately, the company also showcased “AI Sandbox,” a range of generative AI tools for creating music and sounds from scratch, based on user prompts.
Generative AI tools such as chatbots and image creators continue to have issues with accuracy, however.
Google search boss Prabhakar Raghavan told employees last month that competitors “may have a new gizmo out there that people like to play with, but they still come to Google to verify what they see there because it is the trusted source, and it becomes more critical in this era of generative AI.”
Earlier this year, Google introduced the Gemini-powered image generator. Users discovered historical inaccuracies that went viral online, and the company pulled the feature, saying it would relaunch it in the coming weeks. The feature has still not been re-released.
New search features
The tech giant is launching “AI Overviews” in Google Search on Monday in the U.S. AI Overviews show a quick summary of answers to the most complex search questions, according to Liz Reid, head of Google Search. For example, if a user searches for the best way to clean leather boots, the results page may display an “AI Overview” at the top with a multi-step cleaning process, gleaned from information it synthesized from around the web.
The company said it plans to introduce assistant-like planning capabilities directly within search. It explained that users will be able to search for something like, “‘Create a 3-day meal plan for a group that’s easy to prepare,'” and you’ll get a starting point with a wide range of recipes from across the web.
As far as its progress to offer “multimodality,” or integrating more images and video within generative AI tools, Google said it will begin testing the ability for users to ask questions through video, such as filming a problem with a product they own, uploading it and asking the search engine to figure out the problem. In one example, Google showed someone filming a broken record player while asking why it wasn’t working. Google Search found the model of the record player and suggested that it could be malfunctioning because it wasn’t properly balanced.
Another new feature being tested is called “AI Teammate,” which will integrate into a user’s Google Workspace. It can build a searchable collection of work from messages and email threads with more PDFs and documents. For instance, a founder-to-be could ask the AI Teammate, “Are we ready for launch?” and the assistant will provide an analysis and summary based on the information it can access in Gmail, Google Docs and other Workspace apps.
Project Astra
Project Astra is Google’s latest advancement toward its AI assistant that’s being built by Google’s DeepMind AI unit. It’s just a prototype for now, but you can think of it as Google’s aim to develop its own version of J.A.R.V.I.S., Tony Stark’s all-knowing AI assistant from the Marvel Universe.
In the demo video presented at Google I/O, the assistant — through video and audio, rather than a chatbot interface — was able to help the user remember where they left their glasses, review code and answer questions about what a certain part of a speaker is called, when that speaker was shown on video.
Google said a truly useful chatbot needs to let users “talk to it naturally and without lag or delay.” The conversation in the demo video happened in real time, without lags. The demo followed OpenAI’s Monday showcase of a similar audio back-and-forth conversation with ChatGPT.
DeepMind CEO Demis Hassabis said onstage that “getting response time down to something conversational is a difficult engineering challenge.”
Pichai said he expects Project Astra to launch in Gemini later this year.
AI hardware
Google also announced Trillium, its sixth-generation TPU, or tensor processing unit — a piece of hardware integral to running complex AI operations — which is to be available to cloud customers in late 2024.
The TPUs aren’t meant to compete with other chips, like Nvidia’s graphics processing units. Pichai noted during I/O, for example, that Google Cloud will begin offering Nvidia’s Blackwell GPUs in early 2025.
Nvidia said in March that Google will be using the Blackwell platform for “various internal deployments and will be one of the first cloud providers to offer Blackwell-powered instances,” and that access to Nvidia’s systems will help Google offer large-scale tools for enterprise developers building large language models.
In his speech, Pichai highlighted Google’s “longstanding partnership with Nvidia.” The companies have been working together for more than a decade, and Pichai has said in the past that he expects them to still be doing so a decade from now.
Technology
A ‘seismic’ Nvidia shift, AI chip shortages and how it’s threatening to hike gadget prices
The logo of an Apple Store is seen reflected on the glass exterior of a Samsung flagship store in Shanghai, China Monday, Oct. 20, 2025.
Wang Gang | Feature China | Future Publishing | Getty Images
The cost of your smartphone might rise, analysts are warning, as the AI boom clogs up supply chains and a recent change by Nvidia to its products could make it worse.
AI data centers, on which tech giants globally are spending hundreds of billions of dollars, require chips from suppliers, like Nvidia, which relies on many different components and companies to create its coveted graphics processing units.
But other companies like AMD, the hyperscalers like Google and Microsoft, and other component suppliers all rely on this supply chain.
Many parts of the supply chain can’t keep up with demand, and it’s slowing down components that are critical for some of the world’s most popular consumer electronics. Those components are seeing huge spikes in prices, threatening price rises for the end product and could even lead to shortages of some devices.
“We see the rapid increase in demand for AI in data centers driving bottlenecks in many areas,” Peter Hanbury, partner in the technology practice at Bain & Company, told CNBC.
Where is the supply chain clogged?
One of the starkest assessments came from Alibaba CEO Eddie Wu, CEO of Chinese tech giant Alibaba.
Wu, whose company is building its own AI infrastructure and designs its own chips, said last week that there are shortages across semiconductor manufacturers, memory chips and storage devices like hard drives.
“There is a situation of undersupply,” Wu said, adding that the “supply side is going to be a relatively large bottleneck.” He added this could last two to three years.
Bain and Co.’s Hanbury said there are shortages of hard disk drives, or HDDs, which store data. HDDs are used in the data center. These are preferred by hyperscalers,: big companies like Microsoft and Google. But, with HDDs at capacity, these firms have shifted to using solid-state drives, or SSDs, another type of storage device.
However, these SSDs are key components for consumer electronics.
The other big focus is on a type of chip under the umbrella of memory called dynamic random-access memory or DRAM. Nvidia’s chips use high-bandwidth memory which is a type of chip that stacks multiple DRAM semiconductors.
Memory prices have surged as a result of the huge demand and lack of supply. Counterpoint Research said it expects memory prices to rise 30% in the fourth quarter of this year and another 20% in early 2026. Even small imbalances in supply and demand can have major knock on effects on memory pricing. And because of the demand for HBM and GPUs, chipmakers are prioritizing these over other types of semiconductors.
“DRAM is certainly a bottleneck as AI investments continue to feed the imbalance between demand and supply with HBM for AI being prioritized by chipmakers,” MS Hwang, research director at Counterpoint Research, told CNBC.
“Imbalances of 1-2% can trigger sharp price increases and we’re seeing that figure hitting 3% levels at the moment – this is very significant.”
Why are there issues?
Building up capacity in various areas of the semiconductor supply chain can be capital-intensive. And it’s an industry that’s known to be risk-averse and did not add the capacity necessary to meet the projections provided by key industry players, Bain & Co.’s Hanbur said.
“The direct cause of the shortage is the rapid increase in demand for data center chips,” Hanbury said.
“Basically, the suppliers worried the market was too optimistic and they did not want to overbuild very expensive capacity so they did not build to the estimates provided by their customers. Now, the suppliers need to add capacity quickly but as we know, it takes 2-3 years to add semiconductor manufacturing fabs.”
Nvidia at the center
A lot of attention is on Nvidia given it dominates when it comes to the chips that are being put into AI data centers.
It is a huge customer of high bandwidth memory, for example. And its products are manufactured by TSMC which also has other major customers like Apple.
But analysts are focused on a change Nvidia has made to its products that has the potential to add major pressure to consumer electronics supply chains. The U.S. giant is increasingly shifting toward using a type of memory in its products called Low-Power Double Data Rate (LPDDR). This is seen as more power efficient than the previous Double Data Rate, or DDR memory.
The problem is, Nvidia is increasingly using the latest generation of LPDDR memory, which is also used by high-end consumer electronics makers such as Samsung and Apple.
Typically, the industry would just be dealing with demand for this product from a handful of big electronics players. But now Nvidia, which has huge scale, is entering the mix.
“We also see a bigger risk on the horizon is with advanced memory as Nvidia’s recent pivot to LPDDR means they’re a customer on the scale of a major smartphone maker — a seismic shift for the supply chain which can’t easily absorb this scale of demand,” Hwang from Counterpoint Research said.
How AI boom is impacting consumer electronics
Here’s the link between all of this.
From chip manufacturers like TSMC, Intel and Samsung, there is only so much capacity. If there is huge demand for certain types of chips, then these companies will prioritize those, especially from their larger customers. That can lead to shortages of other types of semiconductors elsewhere.
Memory chips, in particular DRAM which has seen prices shoot up, is of particular concern because it’s used in so many devices from smartphones to laptops. And this could lead to price rises in the world’s favorite electronics.
DRAM and storage represent around 10% to 25% of the bill of materials for a typical PC or smartphone, according to Hanbury of Bain & Co. A price increase of 20% to 30% in these components would increase the total bill of materials costs by 5% to 10%.
“In terms of timing, the impact will likely start shortly as component costs are already increasing and likely accelerate into next year,” Hanbury said.
On top of this, there is now demand from players involved in AI data centers like Nvidia, for components that would have typically been used for consumer devices such as LPDDR which adds more demand to a supply constrained market.
If electronics firms can’t get their hands on the components needed for their devices because they’re in short supply or going toward AI data centers, then there could be shortages of the world’s most popular gadgets.
“Beyond the rise in cost there’s a second issue and that’s the inability to secure enough components, which constrains the production of electronic devices,” Counterpoint Research’s Hwang said.
What are tech firms saying?
A number of electronics companies have warned about the impact they are seeing from all of this.
Xiaomi, the third-biggest smartphone vendor globally, said it expects that consumers will see “a sizeable rise in product retail prices,” according to a Reuters reported this month.
Jeff Clark, chief operating officer at Dell, this month said the price rises of components is “unprecedented.”
“We have not seen costs move at the rate that we’ve seen,” Clark said on an earnings call, adding that the pressure is seen across various types of memory chips and storage hard drives.
The unintended consequences
The AI infrastructure players are using similar chips to those being used in consumer electronics. These are often some of the more advanced semiconductors on the market.
But there are legacy chips which are manufactured by the same companies that the AI market is relying on. As these manufacturers shift attention to serving their AI customers, there could be unintended consequences for other industries.
“For example, many other markets depend on the same underlying semiconductor manufacturing capabilities as the data center market” including automobiles, industrials and aerospace and defense, which “will likely see some impact from these price increases as well,” Hanbury said.
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