Google is bringing AI to its mapping apps, integrating its Gemini chatbot to enhance user experiences in Google Maps, Waze, and Google Earth. With over two billion active users each month, Google Maps is a core service where the tech giant aims to apply recent advancements in AI to offer more accurate, personalised suggestions. Users can expect responses that better account for specific preferences, such as ‘fun things to do with friends at night’, creating results tailored to time and context.
Previously, Google Maps would deliver generic results that might include attractions not relevant for the time or situation. Now, powered by Gemini, Google Maps can answer more nuanced questions, refining its suggestions for local spots, like late-night music venues or seasonal activities. AI-driven summaries will also be introduced, adding insights on locations based on user reviews and presented alongside existing listings for an enhanced search experience.
Google has faced criticism for the inaccuracies in some AI-generated responses, including one instance of a recipe error. To minimise similar issues with the Maps updates, responses from Gemini will be checked against Google’s verified data sources, offering users more reliable information while making suggestions for their specific needs.
Beyond Google Maps, the company is implementing AI across other mapping tools, such as Google Earth and Waze. In Waze, new voice-activated capabilities will help drivers report incidents hands-free, and in Google Earth, developers and urban planners will be able to use AI chatbots for data analysis. Google’s AI-powered enhancements aim to provide a more streamlined, intuitive experience across its platforms, making travel and navigation easier.
China’s People’s Liberation Army (PLA) has adapted Meta’s open-source AI model, Llama, to create a military-focused tool named ChatBIT. Developed by researchers from PLA-linked institutions, including the Academy of Military Science, ChatBIT leverages an earlier version of Llama, fine-tuned for military decision-making and intelligence processing tasks. The tool reportedly performs better than some alternative AI models, though it falls short of OpenAI’s ChatGPT-4.
Meta, which supports open innovation, has restrictions against military uses of its models. However, the open-source nature of Llama limits Meta’s ability to prevent unauthorised adaptations, such as ChatBIT. In response, Meta affirmed its commitment to ethical AI use and noted the need for US innovation to stay competitive as China intensifies its AI research investments.
China’s approach reflects a broader trend, as its institutions reportedly employ Western AI technologies for areas like airborne warfare and domestic security. With increasing US scrutiny over the national security implications of open-source AI, the Biden administration has moved to regulate AI’s development, balancing its potential benefits with growing risks of misuse.
Coframe, an AI startup focused on optimising websites and marketing, announced it has raised $9.3 million in seed funding. The funding round was co-led by Khosla Ventures and NFDG, the AI fund launched by former GitHub CEO Nat Friedman and ex-Apple executive Daniel Gross. Coframe’s platform uses generative AI to automatically test and refine website content, visuals, and code, enhancing personalisation and boosting user engagement for clients.
CEO Josh Payne noted that Coframe’s recent trial with a major international firm showed impressive results, with campaigns increasing click-through rates by an average of 42%, while some segments saw a 352% improvement. Coframe has also collaborated with OpenAI to develop a specialised AI model that generates custom user interface code, ensuring on-brand and visually consistent website elements.
Currently in a limited testing phase, Coframe is working closely with growth and marketing teams to fine-tune its platform. The company aims to redefine how businesses design user experiences by tailoring website interfaces based on users’ profiles and intent.
Meta Platforms exceeded third-quarter profit and revenue estimates, reporting a profit of $6.03 per share, compared to the projected $5.25. Revenue reached $40.59 billion, just ahead of analysts’ forecasts. However, the company warned of increased infrastructure expenses tied to its AI ambitions, prompting a 2.9% dip in after-hours trading.
The company is navigating heavy spending on AI infrastructure to support new technologies, setting it apart from cloud service providers who typically profit more directly from similar investments. Meta’s expenses for the quarter totalled $23.2 billion, with capital expenditure at $9.2 billion. While it adjusted its annual expense forecast to $96-98 billion, it foresees a rise in depreciation and operating costs due to its expanding data centre fleet.
Meta’s core ad business remains essential to covering its AI investments, and analysts believe holiday ad spending could bolster the company’s earnings further. In the third quarter, Meta’s daily active users across its app family grew 5% to 3.29 billion, while its Reality Labs division saw losses of $4.4 billion, slightly better than expected.
PepsiCo is enhancing data collaboration with major retailers in response to declining sales and shifting consumer preferences toward budget options. The Lay’s and Tostitos maker has seen recent decreases in snack sales volumes, prompting adjustments to product sizes and a renewed focus on advertising. In early October, PepsiCo revised its annual sales forecast, reflecting the need to adapt to current market dynamics.
The data-sharing initiative, led by PepsiCo‘s senior vice president of strategy, Angelika Kipor, enables the company to gain insights into shoppers’ purchasing habits while helping retailers improve their supply chain accuracy. By sharing predictive data, PepsiCo assists retailers in optimising product orders, leading to higher sales—recently seen in collaboration with Carrefour, where the grocer expanded its PepsiCo product range based on historical data insights.
Retailer partnerships also help PepsiCo make data-driven supply chain adjustments using AI, a practice gaining traction among consumer goods companies looking to streamline operations. Kipor emphasised that while data-sharing strengthens trust with retailers, it remains separate from PepsiCo’s pricing negotiations, which have eased since the company’s commitment last year not to implement further price hikes on snacks and drinks despite ongoing inflation.
Toyota and Nippon Telegraph and Telephone (NTT) plan to invest 500 billion yen ($3.27 billion) by 2030 to create an AI-driven platform to reduce traffic accidents. Announced in a joint statement, the Japanese automaker and telecom giant aims to launch the platform by 2028, using extensive data to support driver-assistance technology. This project, initiated amid rising pressure on Japanese automakers to compete in the autonomous driving space, is expected to enhance safety features such as improved visibility in urban areas and smoother expressway merging.
The companies intend the platform to benefit not only their own operations but also government and industry partners, setting a long-term goal to minimise traffic accidents. Toyota and NTT, who first collaborated on 5G-connected car technology in 2017, see this project as part of a broader vision for zero-accident mobility, aiming for widespread adoption by 2030.
Toyota’s existing investments in autonomous technology include Woven by Toyota, a unit established in 2021 focused on AI mobility. Woven by Toyota is also developing the Arene automotive software platform and Woven City, a testing hub in Shizuoka. As part of these advancements, NTT and Toyota also plan to test self-driving technology as early as 2025.
Google Cloud has launched its first in-house Arm-based CPU, called the Axion chip, now available to all cloud customers, including streaming services like Spotify and Paramount. Designed with Arm Holdings technology, the Axion chip offers about 60% greater energy efficiency than traditional processors from Intel and AMD, allowing developers to save power for other intensive tasks, such as AI, according to Mark Lohmeyer, Google Cloud‘s vice president of compute and AI infrastructure.
Google joins Amazon, Microsoft, and Ampere Computing in offering Arm-based processors that provide high performance with lower electricity usage. The Axion chip, delivered via a service called an ‘instance,’ represents Google Cloud’s growing focus on energy-efficient computing solutions. Though Google Cloud has used Ampere’s Arm-based chips in the past, it intends to shift more focus to its own Axion chip as the primary option for cloud customers moving forward.
Google Cloud has already been using the Axion chip internally, powering various cloud services for some time. Lohmeyer stated the Axion chip’s enhanced efficiency and integration into Google’s infrastructure mark a significant milestone in Google’s cloud technology portfolio.
The Malaysia Digital Economy Corporation (MDEC) has signed two significant Memorandums of Understanding (MoUs) with Singapore’s Ascent and Indonesia’s Central Capital Ventura (CCV), aiming to attract up to RM200 million (approximately US$45 million) in capital investment. These strategic partnerships focus on fostering the growth of Malaysian startups in essential sectors such as fintech, healthcare, AI, and robotics while providing opportunities for access to international markets across Southeast Asia.
By emphasising development in key areas like AI, cybersecurity, blockchain, and digital finance, MDEC seeks to support local innovation and talent development, ultimately positioning Malaysia as a dynamic, digital-first nation. The commitment to nurturing local expertise and fostering entrepreneurship is crucial for enhancing Malaysia’s status as a leader in technological advancement within the region.
MDEC is dedicated to ensuring the effective implementation of these initiatives by working closely with Ascent and CCV. The collaboration will maximise the long-term benefits for Malaysia’s digital economy, addressing immediate investment needs while laying the groundwork for sustainable growth.
Coventry University researchers are using AI to support teachers in northern Vietnam‘s rural communities, where access to technology and training is often limited. Led by Dr Petros Lameras, the GameAid project introduces educators to generative AI, an advanced form of AI that creates text, images, and other materials in response to prompts, helping teachers improve lesson development and classroom engagement.
The GameAid initiative uses a game-based approach to demonstrate AI’s practical benefits, providing tools and guidelines that enable teachers to integrate AI into their curriculum. Dr Lameras highlights the project’s importance in transforming educators’ technological skills, while Dr Nguyen Thi Thu Huyen from Hanoi University emphasises its potential to close the educational gap between Vietnam’s urban and rural areas.
The initiative is seen as a key step towards promoting equal learning opportunities, offering much-needed educational resources to under-represented groups. Researchers at Coventry hope that their work will support more positive learning outcomes across Vietnam’s diverse educational landscape.
Big technology firms, including Microsoft and Meta, are significantly increasing their investments in AI data centres to meet soaring demand, but Wall Street is looking for quicker returns on these expenditures. Both companies reported rising capital expenses due to their AI initiatives, with Alphabet also indicating that its costs would remain elevated. Amazon is expected to follow suit in its upcoming earnings report.
This surge in capital spending could impact profit margins, causing concern among investors. Shares of major tech companies, including Meta and Microsoft, fell by around 4% in premarket trading, despite reporting better-than-expected profits for the July-September quarter. Analysts warn that while the race to build AI capacity is intensifying, it will take time for these investments to yield returns.
Microsoft’s capital expenditures for a single quarter now surpass its total annual spending from prior years. The company noted a 5.3% increase in spending, amounting to $20 billion, while also predicting further increases related to AI. However, they warned of potential slowdowns in growth for their Azure cloud business due to data centre capacity constraints. Similarly, Meta anticipates a “significant acceleration” in AI infrastructure costs next year.
The tech industry is experiencing bottlenecks, particularly as chipmakers like Nvidia struggle to keep up with the demand for AI chips. Advanced Micro Devices has also reported that AI chip demand is outpacing supply, limiting growth potential. Despite these challenges, both Microsoft and Meta maintain that it is still early in the AI cycle and emphasise the long-term benefits of their investments, echoing earlier experiences during the development of cloud technology.
