WhatsApp is developing a new AI feature to create user avatars, following in the footsteps of Meta AI. According to WABetaInfo, this ‘Imagine Me’ feature will allow users to generate AI-based avatars by typing prompts in their chats. The feature was discovered in the latest WhatsApp beta for Android 2.24.14.13, available through the Google Play Beta programme.
Users can generate avatars by typing ‘Imagine me’ in the Meta AI chat or ‘@Meta AI imagine me’ in other chats. A screenshot from WABetaInfo shows how this feature might look. Once enabled, users must take setup photos, and the AI will create images based on the provided prompts. The resulting images are automatically shared in the conversation, with user privacy preserved.
The feature is optional and requires users to opt in through their settings. While currently available only in limited countries, it is still under development and cannot yet be tested by all users. WhatsApp aims to make Meta AI a more integral part of daily user interactions with this innovative avatar creation tool.
For the past two years, many unprofitable tech startups have faced significant challenges, leading to cost-cutting, mergers, or closures. However, startups focused on AI have been an exception, thriving amidst this broader downturn. The AI boom, which began in late 2022, has now become a strong counterpoint to the struggling startup landscape.
In the second quarter of this year, investors poured $27.1 billion into AI startups in the United States, nearly half of all US startup funding during that period. This surge in investment has driven overall startup funding to $56 billion, marking a 57% increase from the previous year and the highest three-month total in two years. AI companies are attracting significant funding, reminiscent of the tech investment frenzy of 2021.
Large financing rounds have bolstered the AI sector’s overall deal-making activity. Notable examples include CoreWeave raising $1.1 billion and later $7.5 billion in debt, Scale AI securing $1 billion, and xAI, founded by Elon Musk, obtaining $6 billion. Furthermore, this influx of capital has prompted venture capital investors to shift their focus, encouraging startups to aggressively pursue growth, particularly in AI.
Despite the excitement, building AI technology is expensive, requiring substantial investment in powerful computer chips and cloud storage. A recent analysis showed that AI startups spend an average of 22% of their computing costs, more than double that of non-AI software companies. As AI’s potential continues to generate significant hype, competition from big tech firms like Microsoft and Amazon may impact the ability of AI startups to secure such large sums in the future.
According to a European Commission report, the EU must catch up to its 2030 AI targets. The investigation into the EU’s Digital Decade project revealed that only 11% of the EU enterprises currently use designated AI technologies, far short of the 75% target set for 2030. At this rate, the Commission estimates it would take almost a century to achieve this goal.
The report also highlighted other areas for improvement, such as the EU being over a decade behind in producing the desired number of tech unicorns and spreading basic tech skills among the general public. Despite these setbacks, European Commission leaders remain optimistic, pointing out that the report offers a clear path forward. Margrethe Vestager, the EC’s competition commissioner, stressed the need for increased State-level investments to reach the digital transformation targets.
Thierry Breton, the EU’s digital chief, echoed these sentiments, emphasising the importance of investments, cross-border cooperation, and the completion of the Digital Single Market to boost the adoption of key technologies like AI. The findings come amid concerns that the EU’s stringent AI regulations could hinder its global competitiveness, especially compared to less regulated regions like the US and China.
A senior executive at Chinese tech giant Huawei dismissed concerns that a shortage of advanced AI chips would hinder China’s leadership in AI. Zhang Ping’an, CEO of Huawei Cloud, acknowledged China’s computing power limitations but emphasised the need for innovation over-reliance on the most advanced AI chips. His comments come amid tighter US restrictions on AI chip shipments to China, including bans on sales from companies like Nvidia.
Speaking at the World AI Conference in Shanghai, Zhang urged a shift in perspective, stating that the absence of cutting-edge AI chips shouldn’t be seen as a barrier to leading in AI. He highlighted Huawei’s development of its AI chip, Ascend, which is widely used in China for training AI models despite being less powerful than Nvidia’s offerings.
Zhang advocated for innovative approaches leveraging the cloud to overcome the lack of advanced chips, suggesting that combining cloud, edge, and network technologies can enhance efficiency and reduce energy consumption. He also positioned Huawei Cloud as a leader in providing these innovative solutions.
China leads the world in generative AI patent requests, significantly outpacing the United States, according to the UN’s World Intellectual Property Organization (WIPO). The technology, which has surged in public awareness since late 2022, was linked to approximately 54,000 inventions over the past decade. More than a quarter of these were filed just last year, highlighting the rapid growth and interest in generative AI.
WIPO’s report, the first of its kind, aims to track trends in generative AI development through patent applications. Over 38,200 generative AI inventions originated from China in the past decade, far surpassing the nearly 6,300 from the USA. South Korea, Japan, and India followed with significantly fewer patents. Generative AI, which includes tools like ChatGPT, Google Gemini, and Baidu’s Ernie, is utilised across various industries, including life sciences, manufacturing, and telecommunications.
Despite the many patents, WIPO cautions that quantity does not equate to quality. It remains uncertain which patents will hold market value or have a transformative impact on society. While the US and China are often seen as rivals in AI development, US tech companies currently lead the production of cutting-edge AI systems. In 2023, US-based institutions produced 61 notable machine-learning models, compared to 21 from the EU and 15 from China. The US also leads in AI foundation models and private AI investments.
Although Judy Garland never recorded herself reading ‘The Wonderful Wizard of Oz,’ fans will soon be able to hear her rendition thanks to a new app by ElevenLabs. The AI company has launched the Reader app, which can convert text into voice-overs using digitally produced voices of deceased celebrities, including Garland, James Dean, and Burt Reynolds. The app can transform articles, e-books, and other text formats into audio.
Dustin Blank, head of partnerships at ElevenLabs, emphasised the company’s respect for the legacies of these celebrities. The company has made agreements with the estates of the actors, though compensation details remain undisclosed. That initiative highlights AI’s potential in Hollywood, especially for creating content using synthetic voices, but it also raises important questions about the licensing and ethical use of AI.
The use of AI-generated celebrity voices comes amid growing concerns about authenticity and copyright in creative industries. ElevenLabs had previously faced scrutiny when its tool was reportedly used to create a fake robocall from President Joe Biden. Similar controversies have arisen, such as OpenAI’s introduction of a voice similar to Scarlett Johansson’s, which she publicly criticised.
As AI technology advances, media companies are increasingly utilising it for voiceovers. NBC recently announced the use of an AI version of sportscaster Al Michaels for Olympics recaps on its Peacock streaming platform, with Michaels receiving compensation. While the market for AI-generated voices remains uncertain, the demand for audiobooks narrated by recognisable voices suggests a promising future for this technology.
Meta is set to integrate more generative AI technology into its virtual, augmented, and mixed-reality games, aiming to boost its struggling metaverse strategy. According to a recent job listing, the company plans to create new gaming experiences that change with each playthrough and follow unpredictable paths. The initiative will initially focus on Horizon, Meta’s suite of metaverse games and applications, but could extend to other platforms like smartphones and PCs.
These developments are part of Meta’s broader effort to enhance its metaverse offerings and address the financial challenges faced by Reality Labs, the division responsible for its metaverse projects. Despite selling millions of Quest headsets, Meta has struggled to attract users to its Horizon platform and mitigate substantial operating losses. Recently, the company began allowing third-party manufacturers to license Quest software features and increased investment in metaverse gaming, spurred by CEO Mark Zuckerberg’s growing interest in the field.
Meta’s interest in generative AI is not new. In 2022, Zuckerberg demonstrated a prototype called Builder Bot, which allows users to create virtual worlds with simple prompts. Additionally, Meta’s CTO, Andrew Bosworth, has highlighted the potential of generative AI tools to democratise content creation within the metaverse, likening their impact to that of Instagram on personal content creation.
Generative AI is already making waves in game development, with companies like Disney-backed Inworld using the technology to enhance game dialogues and narratives. While some game creators are concerned about the impact on their jobs, Meta is committed to significant investments in generative AI, even though CEO Zuckerberg cautioned that it might take years for these investments to become profitable.
Google’s annual sustainability report reveals a nearly 50% increase in greenhouse gas emissions from 2019 to 2024, primarily due to its data centres and supply chain. The 2024 Environmental Report indicates that Google emitted 14.3 million tons of CO2 equivalent last year, raising concerns about its goal to be net zero by 2030. The company expects emissions to rise further before declining, attributing this trend to the growing energy demands of AI integration and increased investment in technical infrastructure.
Efforts to make data centres more efficient, such as using a new generation of tensor processing units (TPUs), have been offset by the rising energy consumption required for AI. Scope 2 emissions, mainly from data centre electricity use, increased by 37% compared to 2022. The rise outpaced the company’s ability to implement carbon-free energy projects, particularly in the United States and Asia-Pacific region. Differences between Google’s global approach to carbon-free energy and the regional guidelines of the GHG Protocol have also contributed to this mismatch.
Scope 3 emissions, which account for 75% of Google’s overall emissions, rose by 8% year-on-year. These indirect emissions from the supply chain are expected to continue increasing due to capital expenditures and investments in AI-related infrastructure. A single generative AI query consumes nearly ten times the power of a regular Google search, highlighting the significant energy demands of AI technology.
Why does it matter?
Additionally, Google’s data centres consume more than three times the amount of water that Microsoft does to remain cool, underscoring the environmental challenges posed by the tech giant’s operations. The report suggests that while Google is making strides in efficiency, the rapid growth of AI and its associated infrastructure presents significant sustainability challenges.
A recent research paper from Google reveals that generative AI already distorts socio-political reality and scientific consensus. The paper, titled ‘Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data,’ was co-authored by researchers from Google DeepMind, Jigsaw, and Google.org.
It categorises various ways generative AI tools are misused, analysing around 200 incidents reported in the media and academic papers between January 2023 and March 2024. Unlike warnings about hypothetical future risks, this research focuses on the real harm generative AI is currently causing, such as flooding the internet with generated text, audio, images, and videos.
The researchers found that most AI misuse involves exploiting system capabilities rather than attacking the models themselves. However, this misuse blurs the lines between authentic and deceptive content, undermining public trust. AI-generated content is being used for impersonation, creating non-consensual intimate images, and amplifying harmful content. These activities often uphold the terms of service of AI tools, highlighting a significant challenge in regulating AI misuse.
Google’s research also emphasises the environmental impact of generative AI. The increasing integration of AI into various products drives energy consumption, making it difficult to reduce emissions. Despite efforts to improve data centre efficiency, the overall rise in AI use has outpaced these gains. The paper calls for a multi-faceted approach to mitigate AI misuse, involving collaboration between policymakers, researchers, industry leaders, and civil society.
According to Sabine Keller-Busse, head of the Swiss bank’s domestic business, UBS is experiencing a significant shift in AI-driven client interactions. She compared this change to patients visiting doctors with pre-formed ideas about their ailments, noting that clients now use AI to generate proposals for the bank.
Speaking at the Point Zero Forum in Zurich, Keller-Busse highlighted the impact of tools like ChatGPT in making more data available, emphasising that UBS must adapt to this new client behaviour.
The bank has been integrating AI into its services and products, launching a pilot programme last year for instant credit aimed at small and mid-sized businesses with urgent liquidity needs. However, this service allows the process to bypass credit officers, expediting the approval for standard credit products. Keller-Busse described this as the beginning of AI’s transformative potential in the banking industry.
As AI continues to evolve, UBS is keenly aware of its growing role in shaping client interactions and service delivery. The bank’s early adoption of AI-driven solutions demonstrates its commitment to leveraging technology to meet its clients’ changing needs, promising future innovations.
