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Lyft Partners with Anthropic for AI-Powered Customer Care

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Lyft (LYFT.O) announced on Thursday that it has partnered with Amazon (AMZN.O) and Alphabet-backed startup Anthropic to introduce artificial intelligence tools to enhance its customer care operations. The company has already been using Anthropic’s Claude AI model, which is integrated with Amazon’s Bedrock generative AI platform. This collaboration has reportedly reduced average customer service resolution times by 87%, allowing the platform to address thousands of customer inquiries daily.

Despite concerns about AI-driven job losses, Lyft emphasized that the goal is not to replace human workers but to enhance the quality and efficiency of its customer support services. Lyft’s approach involves initially addressing customer issues with the AI assistant, directing users to human agents only if further assistance is required.

“We see AI as an opportunity to improve the quality and effectiveness of our operations, not to reduce headcount,” said Jason Vogrinec, Lyft’s executive vice president of platforms. However, industry experts have pointed out that AI models can sometimes produce incorrect or fabricated information, limiting their ability to completely replace human agents. Lyft also noted that complex issues such as safety concerns, account deactivations, and fraud will still be handled by human representatives.

Through this collaboration, Lyft and Anthropic plan to explore additional AI-driven tools for both riders and drivers. Anthropic will also provide training for Lyft’s engineers on the technology, further enhancing the platform’s AI capabilities.

Lyft is scheduled to report its quarterly earnings after market close on Tuesday.

 

Google Ends Diversity Hiring Targets and Reviews DEI Programs

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Google has announced the removal of its diversity-based hiring targets, marking a shift in its approach to diversity, equity, and inclusion (DEI) efforts. The company also revealed that it is reviewing its DEI initiatives, joining other U.S. businesses that are scaling back similar programs.

In an email to staff, Fiona Cicconi, Alphabet’s chief people officer, explained that the company’s previous “aspirational” hiring goals, set in 2020, would no longer be pursued. These goals aimed to increase representation, particularly in offices outside of California and New York. In 2020, CEO Sundar Pichai had set a target to have 30% of Google’s leadership positions filled by people from underrepresented groups by 2025. However, recent updates on this goal were not provided in Alphabet’s annual filing to the SEC, which also saw the removal of a statement that previously emphasized the company’s commitment to diversity.

Google had been at the forefront of promoting inclusive policies, particularly after the 2020 protests against racial injustice. At the time, the company faced criticism from some within its ranks, including a prominent AI leader, who criticized the diversity efforts. Despite some progress in reaching its goals, such as meeting 60% of its five-year target, Google is now shifting its focus away from setting specific diversity targets.

The move has drawn backlash from some workers and activists, including Parul Koul, president of the Alphabet Workers Union (AWU), who criticized the company’s decision as a setback for progress made in the tech industry. Koul also expressed concerns over broader anti-worker trends, particularly from right-wing groups targeting DEI efforts.

In addition to its internal changes, Google is reviewing its DEI programs in light of recent U.S. court decisions and Executive Orders that have impacted federal contractors’ obligations around diversity initiatives. However, the company will maintain internal employee resource groups, such as “Trans at Google,” “Black Googler Network,” and “Disability Alliance,” which will continue to influence product and policy decisions.

This move aligns with similar actions taken by other major tech companies. Meta Platforms, for example, announced in January that it was ending its DEI programs, and Amazon also signaled a reduction in its diversity efforts.

 

Google Introduces New Class of Cheap AI Models as Cost Concerns Intensify

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Google has introduced new, cost-effective AI models under its Gemini family, responding to increasing competition and concerns over the escalating costs of artificial intelligence. The new offerings, including the “Flash-Lite” model, are designed to compete with cheaper AI models like DeepSeek’s, a Chinese rival that has drawn attention for its low-cost AI training.

The company unveiled several versions of its Gemini 2.0 models, which offer varying levels of performance and pricing. Among these is the “Gemini 2.0 Flash,” which was released to the general public after being previewed to developers in December. Flash-Lite, a more affordable variant, has been developed in response to positive feedback on the earlier Flash 1.5 model. However, the cost of Gemini 2.0 Flash is higher than its predecessor.

Google’s new pricing strategy comes amid growing scrutiny from investors over the rising expenses of AI model development. Recently, DeepSeek revealed it spent just $6 million on the final training run of one of its models, prompting comparisons to the significantly higher costs cited by major U.S. AI firms, including Alphabet, Microsoft, and Meta. Despite this, DeepSeek’s low-cost model has spurred competitors to accelerate their AI spending, leading to concerns about the long-term profitability of such investments.

Pricing for Gemini Flash-Lite is competitive, with certain inputs costing as little as $0.019 per 1 million tokens. This is cheaper than OpenAI’s flagship model, which costs $0.075 per million tokens, and slightly higher than DeepSeek’s $0.014 model (though DeepSeek’s pricing will rise fivefold on February 8).

These updates reflect Alphabet’s response to the growing pressure to provide affordable AI models while maintaining a competitive edge in the rapidly evolving AI space. However, despite these advancements, investor concerns remain about the sustainability of high capital expenditures in AI development.