Artificial intelligence Archives | Page 657 of 702

AI-powered workplace innovation: Tech Mahindra partners with Microsoft

Tech Mahindra has partnered with Microsoft to enhance workplace experiences for over 1,200 customers and more than 10,000 employees across 15 locations by adopting Copilot for Microsoft 365. The collaboration aims to boost workforce efficiency and streamline processes through Microsoft’s trusted cloud platform and generative AI capabilities. Additionally, Tech Mahindra will deploy GitHub Copilot for 5,000 developers, anticipating a productivity increase of 35% to 40%.

Mohit Joshi, CEO and Managing Director of Tech Mahindra, highlighted the transformative potential of the partnership, emphasising the company’s commitment to shaping the future of work with cutting-edge AI technology. Tech Mahindra plans to extend Copilot’s capabilities with plugins to leverage multiple data sources, enhancing creativity and productivity. The focus is on increasing efficiency, reducing effort, and improving quality and compliance across the board.

As part of the initiative, Tech Mahindra has launched a dedicated Copilot practice to help customers unlock the full potential of AI tools, including workforce training for assessment and preparation. The company will offer comprehensive solutions to help customers assess, prepare, pilot, and adopt business solutions using Copilot for Microsoft 365, providing a scalable and personalised user experience.

Judson Althoff, Executive Vice President and Chief Commercial Officer at Microsoft, remarked that the collaboration would empower Tech Mahindra’s employees with new generative AI capabilities, enhancing workplace experiences and increasing developer productivity. The partnership aligns with Tech Mahindra’s ongoing efforts to enhance workforce productivity using GenAI tools, demonstrated by the recent launch of a unified workbench on Microsoft Fabric to accelerate the adoption of complex data workflows.

ChatGPT vs Google: The battle for search dominance

OpenAI’s ChatGPT, launched in 2022, has revolutionised the way people seek answers, shifting from traditional methods to AI-driven interactions. This AI chatbot, along with competitors like Anthropic’s Claude, Google’s Gemini, and Microsoft’s CoPilot, has made AI a focal point in information retrieval. Despite these advancements, traditional search engines like Google remain dominant.

Google’s profits surged by nearly 60% due to increased advertising revenue from Google Search, and its global market share reached 91.1% in June, even as ChatGPT’s web visits declined by 12%.

Google is not only holding its ground but also leveraging AI technology to enhance its services. Analysts at Bank of America credit Gemini, Google’s AI, with contributing to the growth in search queries. By integrating Gemini into products such as Google Cloud and Search, Google aims to improve their performance, blending traditional search capabilities with cutting-edge AI innovations.

However, Google’s dominance faces significant legal challenges. The U.S. Department of Justice has concluded a major antitrust case against Google, accusing the company of monopolising the digital search market, with a verdict expected by late 2024.

Additionally, Google is contending with another antitrust lawsuit filed by the U.S. government over alleged anticompetitive behaviour in the digital advertising space. These legal challenges could reshape the digital search landscape, potentially providing opportunities for AI chatbots and other emerging technologies to gain a stronger foothold in the market.

User concerns grow as AI reshapes online interactions

As AI continues to evolve, it’s reshaping online platforms and stirring concerns among longtime users. At a recent tech conference, concerns were raised about AI-generated content flooding forums like Reddit and Stack Overflow, mimicking human interactions. Reddit moderator Sarah Gilbert highlighted the frustration felt by many contributors who see their genuine contributions overshadowed by AI-generated posts.

Stack Overflow, a hub for programming solutions, faced backlash when it initially banned AI-generated responses due to inaccuracies. However, it’s now embracing AI through partnerships to enhance user experience, sparking debates about the balance between human input and AI automation. CEO Prashanth Chandrasekar acknowledged the challenges, noting their efforts to maintain a community-driven knowledge base amidst technological shifts.

Meanwhile, social media platforms like Meta (formerly Facebook) are under scrutiny for using AI to train models on user-generated content without explicit consent. That has prompted regulatory action in countries like Brazil, where fines were imposed for non-compliance with data protection laws. In Europe and the US, similar concerns over privacy and transparency persist as AI integration grows.

The debate underscores broader issues of digital ethics and the future of online interaction, where authenticity and user privacy collide with technological advancements. Platforms must navigate these complexities to retain user trust while embracing AI’s potential to innovate and automate online experiences.

AI stocks surge prompts profit-taking advice

According to strategists at Citigroup Inc., investors are being advised to consider cashing in on the recent surge in AI stocks. The analysis highlights strong investor sentiment towards AI-exposed equities, reminiscent of levels seen in 2019. Drew Pettit’s team at Citi notes that while there’s no clear bubble in AI stocks overall, the rapid rise in specific names raises concerns about increased volatility ahead.

This year, the AI frenzy has driven Nvidia Corp. to briefly claim the title of the world’s most valuable company, while Taiwan Semiconductor Manufacturing Co. surpassed $1 trillion in market value. Citi suggests focusing on profit-taking, particularly among chip-makers, and diversifying investments across the broader AI sector.

Despite cautious signals from Citi, many market observers believe the AI momentum will persist through the year’s second half. Bloomberg News reports a split among investors, some favouring established giants like Nvidia, while others look to secondary beneficiaries such as utilities and infrastructure providers.

Acknowledging AI stocks’ optimism, Citi’s strategists emphasise that current stock prices imply high expectations.

Singapore advocates for international AI standards

Singapore’s digital development minister, Josephine Teo, has expressed concerns about the future of AI governance, emphasising the need for an internationally agreed-upon framework. Speaking at the Reuters NEXT conference in Singapore, Teo highlighted that while Singapore is more excited than worried about AI, the absence of global standards could lead to a ‘messy’ future.

Teo pointed out the necessity for specific legislation to address challenges posed by AI, particularly focusing on using deepfakes during elections. She stressed that implementing clear and effective laws will be crucial as AI technology advances to manage its impact on society and ensure responsible use.

Singapore’s proactive stance on AI reflects its commitment to balancing technological innovation with necessary regulatory measures. The country aims to harness the benefits of AI while mitigating potential risks, especially in critical areas like electoral integrity.

Tech giants promote AI-powered PCs

Tech giants like Microsoft and Qualcomm are aggressively promoting a new category of computers dubbed ‘AI PCs,’ which boast integrated AI capabilities. These machines feature dedicated processors designed to enhance AI functions such as personal assistants and task automation, distinguishing them from standard laptops and desktops.

Despite the hype, only a tiny fraction—just 3%—of PCs shipped this year meet Microsoft’s stringent processing power criteria to qualify as AI PCs, according to IDC. Analysts remain sceptical about the practical utility of these AI features, noting limited software support beyond Microsoft’s ecosystem. Major developers like Adobe, Salesforce, and SentinelOne have hesitated to optimise their applications for AI PCs, preferring to deliver AI capabilities via cloud services.

While some smaller software firms have tailored their apps for on-device AI, more considerable adoption hurdles persist. Initial reviews highlight that current AI functionalities on these PCs, such as eye-tracking during video calls and generative AI content creation, are often seen as gimmicks rather than transformative tools. Furthermore, privacy concerns delayed the rollout of flagship AI features like Microsoft’s Recall.

Why does this matter?

Despite challenges, industry players are optimistic about the potential of AI PCs to rejuvenate the stagnant PC market. With superior battery life and promises of enhanced performance, these devices aim to entice consumers who last upgraded at the pandemic’s onset. Market data from Circana indicates early traction, particularly among tech-savvy users and content creators.

Looking ahead, Qualcomm, vying to challenge Intel’s dominance in PCs, plans to market its Snapdragon processors for AI PCs aggressively. Intel and AMD are expected to release competing models later this year, addressing compatibility issues that currently limit adoption. Industry analysts project AI PCs to comprise about 20% of new PC shipments by 2026, signalling a slow but steady shift towards AI-enhanced computing solutions.

OpenAI blocks Chinese users amid growing tech rivalry

At the recent World AI Conference in Shanghai, China’s leading AI company, SenseTime, unveiled its latest model, SenseNova 5.5, which can identify objects, provide feedback on drawings, and summarise text. Comparable to OpenAI’s GPT-4, SenseNova 5.5 aims to attract users with 50 million free tokens and free migration support from OpenAI services. The launch of SenseNova 5.5 comes at a crucial time, as OpenAI will block Chinese users from accessing its tools starting 9 July, intensifying the rivalry between US and Chinese AI firms.

OpenAI’s decision to block Chinese users has sparked concern in China’s AI community, raising questions about equitable access to AI technologies. However, it has also created an opportunity for Chinese companies like SenseTime, Baidu, Zhipu AI, and Tencent Cloud to attract new users with free tokens and migration services, accelerating the development of Chinese AI companies that are already engaged in fierce competition.

Why does this matter?

The US-China tech rivalry has led to US restrictions on exporting advanced semiconductors to China, impacting the AI industry’s growth. While Chinese companies are quickly advancing, the US sanctions are causing shortages in computing capacity, as seen with Kuaishou’s AI model restrictions. Despite these challenges, Chinese commentators view OpenAI’s departure as a chance for China to achieve greater technological self-reliance and independence.

AI cybersecurity in devices deemed high-risk by European Commission

AI-based cybersecurity and emergency services components in internet-connected devices are expected to be classified as high-risk under the AI Act, according to a European Commission document seen by Euractiv. The document, which interprets the relationship between the 2014 Radio Equipment Directive (RED) and the AI Act, marks the first known instance of how AI-based safety components will be treated under the new regulations. The RED pertains to wireless devices, including those using Wi-Fi and Bluetooth, beyond traditional radios.

Under the AI Act, high-risk AI systems will be subject to extensive testing, risk management, security measures, and documentation. The Act includes a list of use cases where AI deployment is automatically considered high-risk, such as in critical infrastructure and law enforcement. It also sets criteria for categorising other high-risk products, requiring third-party conformity assessments in line with sector-specific regulations. AI cybersecurity and emergency services components meet these criteria under the RED, thus being classified as high-risk.

Even in cases where the RED allows for self-assessment compliance with harmonised standards, these AI-based components are still deemed high-risk. The AI Act references numerous sectoral regulations that could classify AI products as high-risk, extending beyond electronics to medical devices, aviation, heavy machinery, and personal watercraft. The preliminary interpretation suggests that self-assessment standards are insufficient to remove the high-risk classification from AI products in these industries.

The AI Act imposes significant requirements on high-risk AI systems, while those not in this category face only minor transparency obligations. The Commission’s document is a preliminary interpretation, and the full application of the AI Act, which spans over 500 pages, remains to be seen. Despite initial estimates that 5-15% of AI systems would be classified as high-risk, a 2022 survey of EU-based startups indicated that 33-50% of these startups consider their products high-risk. Further interpretive work is needed to understand how the AI Act will impact various sectors.

Why does it matter?

The abovementioned proceedings highlight the European Commission’s stringent approach to regulating AI-based cybersecurity and emergency services in internet-connected devices. By classifying these components as high-risk, the AI Act mandates rigorous testing, security measures, and documentation, ensuring robust safety standards. This move underscores the EU’s commitment to protecting critical infrastructure and sensitive data and signals significant regulatory implications for various industries, potentially influencing global standards and practices in AI technology.

AI app aids pastors with sermons

A new AI platform called Pulpit AI, designed to assist pastors in delivering their sermons more effectively, is set to launch on 22 July. Created by Michael Whittle and Jake Sweetman, the app allows pastors to upload their sermons in various formats such as audio, video, manuscript, or outline. The app generates content like devotionals, discussion questions, newsletters, and social media posts. The aim is to ease the workload of church staff while enhancing communication with the congregation.

Whittle and Sweetman, who have been friends for over a decade, developed the idea from their desire to extend the impact of a sermon beyond Sunday services. They believe Pulpit AI can significantly benefit pastors who invest substantial time preparing sermons by repurposing their content for broader use without additional effort. This AI tool does not create sermons but generates supplementary materials based on the original sermon, ensuring the content remains faithful to the pastor’s message.

Despite the enthusiasm, some, like Dr Charlie Camosy from Creighton University, urge caution in adopting AI within the church. He suggests that while AI can be a valuable tool, it is crucial to consider its long-term implications on human interactions and the traditional processes within the church. Nonetheless, pastors who have tested Pulpit AI, such as Pastor Adam Mesa of Patria Church, report significant benefits in managing their communication and expanding their outreach efforts.

Researchers develop a method to improve reward models using LLMs for synthetic critiques

Researchers from Cohere and the University of Oxford have introduced an innovative method to enhance reward models (RMs) in reinforcement learning from human feedback (RLHF) by leveraging large language models (LLMs) for synthetic critiques. The novel approach aims to reduce the extensive time and cost associated with human annotation, which is traditionally required for training RMs to predict scores based on human preferences.

In their paper, ‘Improving Reward Models with Synthetic Critiques’, the researchers detailed how LLMs could generate critiques that evaluate the relationship between prompts and generated outputs, predicting scalar rewards. These synthetic critiques improved the performance of reward models on various benchmarks by providing additional feedback on aspects like instruction following, correctness, and style, leading to better assessment and scoring of language models.

The study highlighted that high-quality synthetic critiques significantly increased data efficiency, with one enhanced preference pair as valuable as forty non-enhanced pairs. The approach makes the training process more cost-effective and has the potential to match or surpass traditional reward models, as demonstrated by GPT-4.0’s performance in certain benchmarks.

As the field continues to explore alternatives to RLHF, including reinforcement learning from AI feedback (RLAIF), this research indicates a promising shift towards AI-based critiquing, potentially transforming how major AI players such as Google, OpenAI, and Meta align their large language models.