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Forbes
a day ago
- Business
- Forbes
Uber Is Making A Push In Data Labeling After Scale AI's Deal With Meta
Uber is making a push in data labeling. Last week, Scale AI's bombshell deal for Meta to take a 49% stake in the company sent shockwaves throughout the industry: In its wake, prominent clients like OpenAI have pulled back on working with Scale, which the ChatGPT maker had already been doing for months. Google is also planning its split. And a host of data-labeling rivals has been emboldened to step in to fill the void. Among them is a little-known unit from a familiar giant: Uber. Since last November, the ride-hailing behemoth has operated Uber AI Solutions, a data-labeling platform focused on training AI models for enterprise clients. Now as Scale's deal has carved a new opening in the market, Uber is making its pitch to new customers. 'For Uber, our core has always been being the platform of choice for flexible on-demand work,' Megha Yethadka, general manager of the unit and a 10-year veteran of the company, told Forbes. Uber drivers, of course, are contractors that shuttle around passengers and deliveries all across the globe. 'That extends itself really well to this business of digital tasks now.' On Friday, Uber told Forbes it's making a push to expand the service. Among the updates: a new service that provides ready-to-use datasets, including audio, video, images and text, to customers training their own models. The company will also license out the platforms it uses internally for managing data labeling projects and accessing its network of contracted clickworkers, making them available for clients to use. Beyond just training models, Uber is now also offering clients tools to develop AI agents, which can take specific actions for users, like helping with customer support. Another change: Launched as Uber Scaled Solutions, the company recently swapped out the 'scaled' in its name for 'AI.' Yethadka said the rebrand had nothing to do with avoiding confusion with its similarly-named rival, but wanting to more simply convey the AI of the unit. Going forward, Uber wants to separate itself from its data-labeling rivals by automating more of the process to set up clickwork projects. The company is developing a software interface that allows clients 'to simply describe their data needs in plain language,' while the platform automatically handles assigning tasks, setting up workflows and maintaining quality control. The idea is to hand over the project to human clickworkers more quickly, instead of doing manual work to onboard workers. 'We do see an opportunity to build this into a meaningful business line for Uber.' The company said Uber AI Solutions is now available in more than 30 countries, an expansion from its five initial launch markets last November, which included the U.S., Canada and India. Since the start of this year, Yethadka said Uber has doubled the number of clickworkers on its platform. She declined to disclose how many taskers are in the company's network overall, but said there are 'tens of thousands' of people working on each topic area of tasks, including STEM, coding and law. The most engaged clickworkers spend about 3 to 4 hours a day performing tasks, which can range from $20 to $200 per hour, depending on the complexity of the work, Yethadka said. The unit has more than 50 corporate customers, including the autonomous vehicle company Aurora and Niantic, the creator of Pokemon Go that recently ditched the games business to pivot to enterprise AI. The expansion comes as Scale's tie-up with Meta has thrown the data labeling industry into a frenzy. As part of the deal, Scale CEO and founder Alex Wang is heading to Meta to lead the tech giant's newly-formed Superintelligence Lab, an effort to compete with other deep-pocketed frontier labs including those from OpenAI, Anthropic and Google. Now, 'a number of companies are, of course, looking to revisit their partner strategy for data,' said Yethadka, aiming to find vendors that are 'neutral and impartial." In the aftermath, smaller rivals, including unicorns Mercor and Turing and startup Invisible Technologies, are clamoring to pounce. But Uber stands out among the competition because of its sheer size and resources, Yethadka argues. 'A lot of companies in this space are a lot smaller, VC-funding dependent,' she said. Meanwhile Uber, which is worth $175 billion and tallied $43.9 billion in revenue last year, is a more reliable long-term bet, Yethadka said. (She declined to break out the data-labeling unit's revenue.) While other companies in the space more resemble service providers, Uber has a long history of shipping products, which brings a different perspective when the company collaborates with customers, she said. 'We have been a product company and an operations company, and have done this for a living ourselves,' said Yethadka. 'We do see an opportunity to build this into a meaningful business line for Uber.' Even Scale had taken notice of Uber before the Meta deal. 'This space is full of opportunities. I think more people are seeing the value of the work we're doing here, which is why even a business like Uber will want to try their hand at the same space,' Xiaote Zhu, GM of Scale's Outlier platform for generative AI clickwork, told Forbes earlier this year. Still, it's not a foregone conclusion that Uber will come out on top, competitors say. The spoils will go to the company that compiles the best pool of clickworkers. 'Data annotation is transitioning towards higher and higher-skilled work,' Brendan Foody, CEO of $2 billion-valued Mercor, told Forbes. 'Uber's success will depend on how effectively they build this high-skilled talent network.' What's more, Uber has its own baggage. For years, the company limped through controversies around regulation and the treatment of its contract drivers. Yethadka said customers have not minded, and that Uber has committed to 'do the right thing' when it comes to data confidentiality and security controls. 'And that continues to be applied to this new line of business as well,' she said.
The Guardian
a day ago
- Business
- The Guardian
BBC threatens legal action against AI startup over content scraping
The BBC is threatening legal action against Perplexity AI, in the corporation's first move to protect its content from being scraped without permission to build artificial intelligence technology. The corporation has sent a letter to Aravind Srinivas, the chief executive of the San Francisco-based startup, saying it has gathered evidence that Perplexity's model was 'trained using BBC content'. The letter, first seen by the Financial Times, threatens an injunction against Perplexity unless it stops scraping all BBC content to train its AI models, and deletes any copies of the broadcaster's material it holds unless it provides 'a proposal for financial compensation'. The legal threat comes weeks after Tim Davie, the director general of the BBC, and the boss of Sky both criticised proposals being considered by the government that could let tech companies use copyright-protected work without permission. 'If we currently drift in the way we are doing now we will be in crisis,' Davie said, speaking at the Enders conference. 'We need to make quick decisions now around areas like … protection of IP. We need to protect our national intellectual property, that is where the value is. What do I need? IP protection; come on, let's get on with it.' The industry would like an opt-in regime, forcing AI companies to seek permission and strike licensing deals with copyright holders before they can use the content to train their models. In October, Rupert Murdoch's Dow Jones, the owner of the Wall Street Journal, filed a lawsuit against Perplexity, accusing it of engaging in a 'massive amount of illegal copying' in a 'brazen scheme … free-riding on the valuable content the publishers produce'. Perplexity told the FT that the BBC's claims were 'manipulative and opportunistic' and that it had a 'fundamental misunderstanding of technology, the internet and intellectual property law'. Perplexity does not build or train foundation models – unlike other companies such as OpenAI, Google and Meta – but provides an interface that allows users to choose between them. The BBC said that parts of its content had been reproduced verbatim by Perplexity. 'Perplexity's tool directly competes with the BBC's own services, circumventing the need for users to access those services,' the corporation said. In October the BBC began registering copyright in its news website in the US, so it is entitled to 'statutory damages in relation to unauthorised use of these copyright works'. In the UK, original proposals published in a consultation indicated that the government could let AI companies scrape content unless media owners opt out, which the industry said would 'scrape the value' out of the £125bn creative industry. Sign up to Business Today Get set for the working day – we'll point you to all the business news and analysis you need every morning after newsletter promotion Lisa Nandy, the culture secretary, has since said that the government has no preferred option regarding AI copyright laws in the UK but promised the creative sector that it would not be harmed by legislation. 'We are a Labour government, and the principle [that] people must be paid for their work is foundational,' she told a media conference earlier this month. 'You have our word that if it doesn't work for the creative industries, it will not work for us.' Publishers including the Financial Times, Axel Springer, Hearst and News Corporation have signed content licensing deals with OpenAI. Reuters has struck a deal with Meta, and the parent of the Daily Mail has an agreement with The Guardian has approached Perplexity for comment.
Forbes
3 days ago
- Business
- Forbes
AI First? Make Sure Your People Understand It First
AI: Educate first. getty AI-first thinking doesn't just spring out of a vacuum. Leaders and employees need to adopt an AI-first mindset that prepares everyone for the changes ahead. This makes training and education about AI more important than anything – and where any AI-first efforts are most likely to get bogged down. Among students, 65% say they had not had the opportunity to take an AI-specific or AI-inclusive courses at their universities, according to a student-run survey published in EdTech. Only three percent felt very confident that their education would help them secure a job in a field involving AI. AI education is still lacking for current employees as well. While the percentage of workers using AI for their jobs increased from eight percent in 2023 to more than one-third (35%) as of this spring, only 31% said their employer-provided training on AI tools, according to a survey released by Jobs for the Future. In addition, AI use appears to an individual endeavor, with a majority (60%) reporting using AI primarily for self-directed learning. The importance of education and training to prepare organizations for an AI future is emphasized by Adam Brotman and Andy Sack, in their latest book, AI First: The Playbook for a Future-Proof Business and Brand. An AI-first policy cannot move forward without education and training, said Brotman, former chief digital officer at Starbucks, and Sack, former adviser to Microsoft CEO Satya Nadella. 'An AI-first mindset requires a commitment to ongoing education about AI technologies and their potential applications," they wrote. "It encourages experimentation and learning from both successes and failures, ensuring that teams stay ahead of technology advancements.' Such programs should begin with programs 'to build proficiency across the organization. These programs should cover AI basics, applications, and potential impacts on various business functions.' Ultimately, AI education and training smooths the way for 'proper governance and process for scaling AI within your company," they added. "You can't effectively advise the company on an appropriate AI use policy or help prioritize potential AI pilots if you don't have a basic understanding of how the foundational AI systems work, versus still needing to improve, or the variety of capabilities and workflows that stem from AI." Brotman and Slack outline the progression for both individuals and their organizations – from experimenting with AI to building an AI-first culture: Notably, an AI-first mindset also borrows from the 'lean' approach to management, emphasizing 'continuous improvement and innovations by building products that customers want through interactive cycles of build, measure, and learning,' Brotman and Slack pointed out. AI-first lean thinking 'starts with identifying the core problem that needs solving and developing a minimum viable product to test hypotheses. Lean thinking is about reducing waste in processes, understanding customer needs through direct feedback, and pivoting strategies based on data and insights.'
Entrepreneur
11-06-2025
- Business
- Entrepreneur
Machaxi Secures $1.5 Million to Expand AI-Powered Badminton Coaching Across India
The funding round was led by Rainmatter, the investment arm of Zerodha, and included participation from Indian badminton legend Prakash Padukone as well as existing backers You're reading Entrepreneur India, an international franchise of Entrepreneur Media. Machaxi, a Bengaluru-based sports-tech startup focused on grassroots coaching, has raised $1.5 million in funding to scale its AI-powered training model and expand operations into three more cities—Hyderabad, Pune, and Chennai. The funding round was led by Rainmatter, the investment arm of Zerodha, and included participation from Indian badminton legend Prakash Padukone as well as existing backers, the company announced in a press release. This strategic infusion of capital marks a pivotal moment for Machaxi as it builds on its vision to standardize and scale grassroots sports coaching across India. Central to this expansion is a collaboration with the Padukone School of Badminton, under which the two entities aim to establish over 1,000 coaching centers nationwide in the next four years. The partnership will feature an AI-based coaching platform developed by Machaxi, designed to support human coaches, not replace them. The system tracks performance, ensures consistency in training methods, and makes coaching scalable even in regions where experienced trainers are in short supply. "I've always believed that the future of Indian badminton lies in structured grassroots development," said Prakash Padukone. "Machaxi's vision to scale coaching while maintaining quality through AI is forward-thinking and impactful. I'm thrilled to partner with them in shaping the next generation of champions." Nithin Kamath, founder of Zerodha and Rainmatter, said the decision to invest was aligned with their broader focus on sustainability and community development. "Machaxi's tech-driven approach to coaching, combined with a solid on-ground strategy, aligns perfectly with our mission at Rainmatter to back sustainable and impactful ventures," Kamath said. Machaxi co-founder Pratish Raj emphasized that the new funding and partnerships are about more than just growth—they're about reshaping India's sports coaching model. "With the support of Rainmatter and the visionary backing of Mr. Padukone, we're working toward a future where every aspiring athlete, no matter where they come from, can train with consistency, purpose, and access to world-class infrastructure," Raj said.
National Post
10-06-2025
- Business
- National Post
The AI Proficiency Crisis: Enterprise AI Investments Jump While AI Skills Flatline
Article content Section's 2025 AI Proficiency Report: Enterprises are investing in AI, but workforce proficiency is stuck in neutral – raising doubts about enterprise ROI Article content PALO ALTO, Calif. — Section's latest AI Proficiency Report reveals that workforce AI proficiency remains dire, despite companies investing in AI deployments at a higher rate over the last 6 months. Since September 2024, employees' general AI proficiency has flatlined, with only 10% of the workforce scoring as AI-proficient. Article content 'Our latest results show that despite some minor progress, there's still way too much friction for employees to get value from AI,' says Greg Shove, CEO of Section. Article content The survey of 5,013 knowledge workers across the U.S., U.K. and Canada – spanning individual contributors to C-suite members – measured respondents on their knowledge, usage, and skill with generative AI tools. Article content The research found that the vast majority of the workforce (90%) doesn't write effective prompts, know how AI works, or use it regularly. Article content 'Despite minor progress, there's still too much friction for employees to get value from AI,' says Greg Shove, CEO of Section. 'When 25% of the workforce doesn't know what to use AI for, companies will not get ROI.' Article content 60% of companies mandate or encourage the use of AI at work, but only 43% provide training, only 35% have clear AI policies, and only 23% have deployed an LLM to all employees. Most of these investments are reserved for leadership – with individual contributors being the least likely to have LLM access, AI tool reimbursement, and AI training. Article content 'Our research echoes what we hear from enterprise organizations: They've rolled out ChatGPT to leadership or a few groups, and stopped there,' Shove says. 'Without widespread deployment, AI vendors will start seeing churn, CEOs will get frustrated by lack of ROI, and workers will be left to figure it out for themselves.' Article content Key findings are highlighted below, and the full results can be found here: Article content The vast majority of workers are not proficient AI users – but they think they are. Article content 90% of workers are AI 'skeptics, novices, and experimenters,' meaning they have poor prompting skills, use AI irregularly, and don't know how AI works. Only 10% of the knowledge workforce scored as AI-proficient, yet 54% scored themselves as proficient AI users. 25% of employees don't know what to use AI for. 28% don't know how to use it at all. Article content Company investments have increased, but not enough. Article content 71% of companies approve of AI use at work but nearly half (48%) have not deployed an LLM. Companies are 12% more likely to reimburse for tools than last year but 35% of the workforce is still paying for AI tools out of pocket. 9% of companies still ban AI completely – though 32% of employees at companies with AI bans still use it. Article content Functions prime for AI disruption aren't using AI to its full effect. Article content HR, the most likely role to own AI upskilling, scores 3.3 out of 10 in prompting ability, and nearly 40% of HR professionals use AI once a month or less. Customer service is the least-proficient function, and 43% say they rarely or never use it. Article content Excitement is up – but it's still outweighed by anxiety and overwhelm. Article content The percentage of employees who say they're excited about AI has doubled since September 2024, from 23% to 46%. But fear is still the predominant emotion, with 54% saying they're anxious or overwhelmed by AI and 32% saying they're afraid of losing their jobs. Article content Section's CEO, Greg Shove, will be unpacking the full results of the survey, and what they mean for knowledge workers and leaders, in a live webinar tomorrow, June 11 at 12 pm ET. Article content About Section Article content Section is an AI transformation and upskilling partner that works with businesses to create custom solutions for AI benchmarking, upskilling, and workflow redesign. Founded in 2019 by Scott Galloway, and led by serial entrepreneur Greg Shove, Section is backed by General Catalyst, Learn Capital, GSV Ventures, Activant, and other individual investors, including Jeff Bewkes and Tim Armstrong. Since its inception, Section has partnered with 300+ enterprise businesses and upskilled 58,000 knowledge workers. Article content Article content Article content Article content Article content Contacts Article content Azalea Dolan Content Manager, Section adolan@ 512-415-5301 Article content Article content Article content
