Instagram is trialling a new feature called ‘AI Studio’, allowing creators to develop AI versions of themselves. Meta CEO Mark Zuckerberg recently revealed on his broadcast channel that the feature is undergoing an initial test phase with selected creators and users in the United States.
Zuckerberg highlighted that AI avatars from popular creators and interest-based AI models will soon appear in Instagram messaging. These AI entities are initially designed to interact within messaging threads and will be clearly marked as AI-generated.
During the broadcast, Zuckerberg demonstrated early examples featuring AI-powered chatbots developed in collaboration with creators such as the team behind the meme account ‘Wasted’ and Don Allen Stevenson III. These chatbots aim to assist creators by engaging with their followers and responding to messages on their behalf.
Creators on Instagram can initiate interactions by tapping the ‘Message’ button, prompting users to acknowledge that the responses may be AI-generated and potentially not entirely accurate or appropriate. Each AI-generated message will be prefaced with ‘AI’ and marked with a ‘beta’ tag, indicating ongoing development and testing.
Meta’s launch of AI Studio last year enabled businesses to create AI chatbots for platforms like Messenger, Facebook, and Instagram. The initiative reflects Meta’s ongoing efforts to integrate advanced AI technologies into its social media platforms, enhancing user engagement and interaction capabilities.
Why does it matter?
The IATSE’s tentative agreement represents a significant step forward in securing fair wages and job protections for Hollywood’s behind-the-scenes workers, ensuring that the rapid advancements in technology do not come at the expense of human employment.
According to industry executives, AI is increasingly seen as a game-changer in the financial services sector, offering significant opportunities for efficiency and client service enhancements. At a recent investor conference hosted by Morningstar in Chicago, discussions highlighted AI’s potential to improve tasks such as explaining portfolio allocations or lending decisions, often influenced by subconscious biases that are difficult for humans to articulate. Zack Kass, formerly with OpenAI, emphasised the potential of AI to enhance these processes, cautioning that careful implementation is crucial to avoid exacerbating existing challenges.
Investors and technology experts believe AI will streamline routine financial tasks, such as compliance form filling and portfolio development, freeing financial professionals to focus more on personalised client interactions and complex problem-solving. Morningstar’s senior research analyst Karen Zaya noted the growing prevalence of AI-powered chatbots in simpler tasks like customer service inquiries but highlighted the complexity of utilising AI for more nuanced financial planning decisions, such as retirement investments.
While AI adoption holds promise, US regulators are actively soliciting public input on its implications for financial inclusion and equity. Treasury Secretary Janet Yellen has cautioned that while AI could reduce transaction costs, it also introduces significant risks that need careful management by financial firms. Despite concerns about job displacement, experts like Margaret Vitrano from ClearBridge Investments argue that AI will likely complement rather than replace human expertise, particularly in software development and customer service roles requiring nuanced decision-making.
Financial advisers like Brenda Ingram in Chicago are optimistic about AI’s potential to streamline mundane tasks such as compliance reporting, anticipating that AI could enhance efficiency and reduce operational costs in the industry. As financial firms navigate the adoption of AI, the emphasis remains on thoughtful implementation to maximise benefits while mitigating risks, ensuring that AI enhances rather than disrupts the client-adviser relationship and operational workflows.
Chinese search engine giant Baidu has introduced an upgraded version of its AI model, Ernie 4.0 Turbo, to stay competitive in China’s AI market. The new feature follows the October 2023 release of Ernie 4, which Baidu claimed had capabilities on par with OpenAI’s GPT-4. The new model will be available to the public through web and mobile interfaces, with developers able to integrate it via Baidu’s Qianfan AI platform. Since its launch, Ernie has amassed 300 million users.
At the same event, Baidu also announced enhancements to its PaddlePaddle AI ecosystem, which now supports 14.65 million developers and serves 370,000 businesses and institutions. The introduction of Ernie 4.0 Turbo comes as OpenAI plans to block access to its API from China and other countries starting 9 July, impacting many Chinese startups relying on OpenAI’s technology. In response, Baidu and other domestic firms like Alibaba have launched initiatives to attract these users by offering free migration services and incentives.
NBC is set to bring sportscaster Al Michaels back to the Olympics with a twist this summer: his voice will be powered by AI. The network announced on Wednesday that AI software will recreate Michaels’ voice to deliver daily recaps of the Summer Games for subscribers of its Peacock streaming platform. That marks a significant milestone for the use of AI by a major media company.
The AI-driven recaps will be part of a new feature called ‘Your Daily Olympic Recap on Peacock,’ offering 10-minute highlight packages. These packages will include event updates, athlete backstories, and other content personalised to subscriber preferences. NBC claims the highlights can be packaged in about 7 million different ways, drawn from 5,000 hours of live coverage from Paris, showcasing the efficiency of AI in delivering tailored content.
Al Michaels expressed initial scepticism about the project but became intrigued after seeing a demonstration. He is being compensated for his involvement. Michaels, known for his long broadcasting career, including the iconic Miracle on Ice Game at the 1980 Winter Olympics, lent his past NBC broadcast audio to train the AI system. NBC assures that all content will be reviewed by a team of editors for factual accuracy and proper pronunciation. The highlights tool will be available on Peacock via web browsers and iOS and iPadOS apps starting 27 July.
With the UK heading to the polls, the role of AI in guiding voter decisions is under scrutiny. ChatGPT, a generative AI tool, has been tested on its ability to provide insights into the upcoming general election. Despite its powerful pattern-matching capabilities, experts emphasise its limitations and potential biases, given that AI tools rely on their training data and accessible online content.
ChatGPT suggested a strong chance of a Labour victory in the UK based on current polling when prompted about the likely outcomes of the election. However, AI’s predictions can be flawed, as demonstrated when a glitch led ChatGPT to declare Labour as the election winner prematurely incorrectly. This incident prompted OpenAI to refine ChatGPT’s responses, ensuring more cautious and accurate outputs.
ChatGPT can help voters navigate party manifestos, outlining the priorities of major parties like Labour and the Conservatives. By summarising key points from multiple sources, the AI aims to provide balanced insights. Nevertheless, the psychological impact of AI-generated single answers remains a concern, as it could influence voter behaviour and election outcomes.
Why does it matter?
The use of AI for election guidance has sparked debates about its appropriateness and reliability. While AI can offer valuable information, the importance of critical thinking and informed decision-making must be balanced. As the election date approaches, voters are reminded that their choices hold significant weight, and participation in the democratic process is crucial.
A new International Monetary Fund (IMF) report reveals that Nigeria and several other developing nations need more digital infrastructure to effectively deploy AI. The shortfall persists despite Nigeria’s recent launch of its first Multilingual Large Language Model (LLM) and unveiling of an AI strategy in April. The IMF’s ‘AI Preparedness Index,’ which evaluates 174 economies, highlights that many developing countries like Nigeria are trailing in AI readiness due to inadequate digital infrastructure.
According to the Index’s interactive map, most African nations, with exceptions like Namibia, Botswana, and South Africa, exhibit low preparedness for AI. Wealthier economies are generally better equipped for AI adoption, and the IMF warns that the disparity could exacerbate existing global inequalities. The report suggests that while AI has the potential to enhance productivity and expand opportunities in countries like Nigeria, it may also widen the gap between those who can leverage the technology and those who cannot.
To address Nigeria’s challenges, the IMF recommends that emerging markets and developing economies invest heavily in digital infrastructure and worker training. For advanced economies, the priority should be on expanding social safety nets and fostering AI innovation and integration. International coordination is also essential to establish regulations that protect against AI risks and abuses while building public trust in the technology.
Amazon’s AWS, the leading global cloud computing provider, is intensifying efforts to draw the public sector into the realm of AI amidst fierce competition with Microsoft and Google in the generative AI domain. The initiative aims to demonstrate AI’s potential to enhance public services across health, security, and non-profit sectors, leveraging technologies like ChatGPT to streamline operations and improve outcomes.
Over two years, AWS has allocated a substantial $50 million fund to support public sector entities in exploring AI applications, offering cloud computing credits, training, and technical expertise to kickstart innovative projects. Currently serving thousands of government agencies, academic institutions, and nonprofits worldwide, AWS seeks to transition AI concepts into practical solutions that can effectively address public sector challenges.
Dave Levy, AWS’s vice president overseeing global public sector operations, highlighted the importance of moving from conceptualisation to implementation in public sector AI projects, underscoring the need for robust support to navigate complexities and achieve meaningful impacts. The push comes amid heightened competition as Microsoft and Google Cloud aggressively pursue public sector AI adoption, aiming to leverage vast datasets and AI capabilities to revolutionise service delivery and operational efficiency.
Amazon’s AWS remains committed to addressing challenges such as data privacy, security, and ethical considerations surrounding AI adoption in the public sector, emphasising rigorous security protocols and readiness for large-scale deployment.
Why does it matter?
As generative AI continues to evolve, AWS’s strategic focus on public sector adoption underscores its belief in AI’s transformative potential, aiming to lead the charge in integrating advanced technologies into governmental and non-governmental organisations worldwide.
A recent report from Citigroup predicts a significant rise in banking profits, driven by the adoption of AI, with projections soaring to nearly $2 trillion by 2028 from the current $1.7 trillion. While AI has traditionally been used to optimise products and boost productivity, its role is expanding to include customer-facing tasks, similar to how ATMs revolutionised cash withdrawals.
Leading this transformation is DeepBrain AI, a startup based in California founded by Eric Seyoung Jang in 2016. Initially focusing on chatbots, the company now develops AI-powered avatars used by major South Korean banks like KB Kookmin Bank to manage frequently asked questions, thereby reducing the workload on human bankers.
Despite concerns that AI could replace human jobs, the Citigroup report and experts suggest that technology adoption historically leads to more job creation. For instance, the number of compliance officers in the United States has tripled since 2000. While AI may alter the nature of banking roles, it is unlikely to eliminate them. Roles are expected to evolve, necessitating new skills that complement AI technologies.
DeepBrain AI continues to innovate, expanding into sectors such as retail and broadcasting. In banking, their AI avatars are transitioning from in-branch kiosks to mobile banking apps, aiming to offer personalised, face-to-face conversational services.
Micron Technology surpassed revenue expectations in the third quarter due to robust demand for its memory chips, particularly in AI applications. However, its fourth-quarter revenue forecast, while meeting expectations, disappointed investors, leading to a 7.2% drop in after-hours trading.
The forecast failed to meet recent optimistic projections fuelled by the AI boom, which tempered market enthusiasm following a significant rise in Micron’s stock price earlier in the month. Micron’s Chief Business Officer emphasised their strategic advantage in AI chip supply, highlighting robust ongoing demand for their products in the years ahead.
Why does it matter?
Micron remains a prominent player in high-bandwidth memory chips essential for advanced AI systems, positioning it strongly in the semiconductor market. The company’s performance typically establishes benchmarks for the broader chip sector, influencing market sentiment toward competitors like Nvidia, whose stock declined following Micron’s earnings report.
Sequoia Capital is leading a $16 million investment in Dust, a French startup founded by former OpenAI researcher Stanislas Polu. Dust specialises in crafting bespoke AI bots for enterprises, leveraging advanced language models like OpenAI’s GPT and Google’s Gemini.
Its solutions cater to various business needs, such as customer support, sales analytics, and software code management. Instead of creating AI models from the ground up, Dust integrates its software with existing AI platforms such as Slack.
Why does it matter?
The funding round was geared towards facilitating Dust’s expansion into the US market and supporting its global ambitions. Despite facing competition from established entities and fellow startups, Dust maintains agility by using its flexibility to thrive in the competitive landscape of AI automation tools.
