Puma just made a smart move by hiring Andreas Hubert, the former tech chief from rival Adidas, as their new Chief Operating Officer starting September 1st.

Hubert spent four years running all the computer systems and technology at Adidas before wrapping up his job there in June. Now he'll be in charge of a much bigger role at Puma, overseeing global sourcing, IT systems, sustainability efforts, product development, and getting products to stores.

Puma's CEO Arthur Hoeld praised Hubert's mix of tech knowledge and business skills. The company thinks his experience will help them run better operations, improve their digital systems, and make their supply chain stronger as they grow.

The timing makes sense for Puma, which has been working hard to refresh its brand and grow sustainably. The company launched a major marketing campaign earlier this year and brought in new leadership for both CEO and North America president roles.

But Puma faces some real challenges right now. They joined over 80 other brands asking President Trump to consider removing tariffs on shoes.

P.S. For those who don’t know where the rivalry between Adidas and Puma comes, read this

President Donald Trump announced plans to put 100% tariffs on computer chips coming from other countries during a White House meeting on Wednesday.

Trump did not say exactly when these tariffs would start or give more details about how they would work.

The White House is already looking into whether computer chip imports hurt America's security and supply chain. This type of study often leads to new taxes on imports. The government has done similar studies on steel, aluminum, and copper before adding tariffs.

On Tuesday, Trump said he would announce tariffs on both computer chips and medicine "in the next week or so." He mentioned that medicine imports might face even higher tariffs of up to 250%.

Trump made this announcement during a meeting where Apple CEO Tim Cook said his company would spend $100 billion more on making things in America over the next four years. Apple had already promised to invest $500 billion earlier this year.

Tesla is shutting down its Dojo supercomputer project and moving away from building its own chips.

The company's Dojo team leader, Peter Bannon, has left Tesla. CEO Elon Musk has ordered the entire program to close down.

About 20 workers from the Dojo team recently joined a new startup called DensityAI. This new company is led by Ganesh Venkataramanan, who used to run Tesla's Dojo project before leaving in 2023. The remaining Dojo workers will move to other computer projects inside Tesla.

The Dojo supercomputer was Tesla's custom system for processing videos from its cars. It was meant to help train the company's self-driving car technology and its Optimus robot project.

But Tesla was also buying lots of computer chips from other companies at the same time. By the end of 2024, Tesla built a huge training system using 50,000 Nvidia H100 chips called Cortex. Last month, Tesla signed a $16.5 billion deal with Samsung for AI chips to use in its cars and robots.

Google has rolled out several updates to its BigQuery data warehouse service to help companies automate more of their data work using AI agents.

The biggest change involves the data engineering agent that Google first showed off in April. This tool used to only handle basic data prep tasks. Now it can build entire data pipelines, change existing ones, and even fix problems when things break. Users can talk to it in plain English and it understands how different data pieces connect together.

Google also moved its data science agent from its free Colab notebook service into BigQuery itself. This lets data scientists create complete workflows that can plan tasks, write code, run it, and show results all in one place.

The company added autonomous vector embeddings to BigQuery. This feature automatically prepares different types of data for AI search without requiring data teams to do all the manual setup work.

Google's AI query engine, which lets people analyze both structured and messy data together, is now available for all customers to test after being limited to select users.

The company also updated its Looker analytics tool with a new code interpreter. This lets business users ask complex questions about their data in normal language without needing help from IT departments. The tool can write Python code behind the scenes and create charts and graphs to show the answers.

Rick Ochs teaches us that Finops and Cost Optimization for AWS is not just technical but also cultural. To succeed, it is essential to balance performance, costs, and collaboration, driving a mindset shift within organizations.

Wells Fargo will use GCP AI agents that can do things like give workers quick market updates, help them find information in long documents, and make customer service smoother.

Right now, about 2,000 Wells Fargo employees are testing Google's AI platform called Agentspace.

Other big banks are doing similar things. BNY has an AI helper called Eliza, and Goldman Sachs is testing an AI agent named Devin that helps write computer code.

Wells Fargo's CEO said the company is still in the early stages of using AI, but they have test programs running in bank branches, phone centers, and other areas where people do manual work.

The bank created a special AI team less than a year ago, led by Tracy Kerrins. She said the new AI tools will help employees work faster and spend more time helping customers with their money goals.

The Trump administration released its AI Action Plan last month, giving business leaders clearer signals about how AI rules will work in America.

Business experts say this lighter touch on rules is making company leaders feel more confident about pushing their AI plans forward. But they still worry about what might happen next and how well these plans will actually work.

Different countries, different rules

Companies working in multiple countries still need to follow each place's AI rules. The US may be going easy on rules, but it still plans to have some requirements around computer security and information sharing between companies.

This feels familiar

The AI rule situation looks a lot like what happened with data privacy laws years ago. Companies that already learned to handle data privacy rules will likely do better with AI rules too. Both require good ways to manage and clean up data.

Checking for unfair treatment

The new plan wants to limit bias in AI systems, but this creates problems. Most AI systems do have unfair biases because they learn from human-created information.

Everyone needs to work together

AI strategy can't just be the technology team's job anymore. Finance, legal, human resources, and other departments all need to work together to make AI plans that will last.

Training workers is key

There aren't enough people who know how to work with AI, and the government plan mentions helping companies train their workers.

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