“Resilient” is the word of the moment on Wall Street.
JPMorgan Chase, Citigroup and Wells Fargo all reported their quarterly earnings Tuesday, and their CEOs all landed independently on the word “resilient” to describe the U.S. economy and its consumers.
“While there have been some signs of a softening, particularly in job growth, the U.S. economy generally remained resilient,” JPMorgan CEO Jamie Dimon said in a statement. Wells Fargo CEO Charlie Scharf said in a news release, “While some economic uncertainty remains, the U.S. economy has been resilient and the financial health of our clients and customers remains strong.” And Citigroup’s CEO, Jane Fraser, said the global economy has “proved more resilient than many anticipated,” and “America’s economic engine is indeed still humming.”
The numbers back them up, to a point. The most recent quarterly GDP data showed the U.S. economy expanding at a faster pace in the second quarter than had been previously expected.
Still, President Donald Trump’s global trade policies continue to fuel uncertainty as tariffs increasingly weigh on consumers. Trillion-dollar company valuations driven in large part by AI raise questions about how long the markets’ record run can continue. Jobs growth has weakened substantially, too.
U.S. stock indexes ended mostly lower Tuesday, with the Nasdaq falling 0.8% and the S&P 500 ending about flat. The 30-stock Dow closed up 200 points. The mixed session followed a dramatic couple days on Wall Street, during which stocks fell sharply on Friday after Trump threatened 100% tariffs on China — only to recover some of those losses Monday.
“There continues to be a heightened degree of uncertainty stemming from complex geopolitical conditions, tariffs and trade uncertainty, elevated asset prices and the risk of sticky inflation,” JPMorgan’s Dimon said.
The jobs market is rapidly cooling, as well, according to government and private data. Payroll processor ADP’s most recent monthly report showed that private employers shed 32,000 jobs in September.
Theofficial government jobs report for the month has been held up by the government shutdown. Before the shutdown, the August jobs report from the Bureau of Labor Statistics showed that employers added just 22,000 jobs for the month. It also revised data to show there was a net loss of jobs in June.
“It’s pretty easy to imagine a world where the labor market deteriorates from here,” JPMorgan’s financial chief, Jeremy Barnum, said on the bank’s conference call.
“The fact that things are fine now doesn’t mean they’re guaranteed to be great forever,” he added.
Despite the dark clouds on the jobs horizon, Barnum said consumers are still — there’s that word again — “resilient,” noting strong spending and lighter-than-expected delinquency rates.
Scharf said Wells Fargo saw spending on debit and credit cards continuing to increase alongside growth in new auto loans.
“The performance of the consumer is just very, very consistent,” he said on Wells Fargo’s earnings call, adding that he didn’t see “any real pockets of slowing.”
At Citigroup, Fraser noted what she called “pockets of valuation frothiness” in the market, and warned that growth may be “cooling somewhat.”
Still, she said, the U.S. “continues to be a pace setter, driven by consistent consumer spending as well as tech investments in AI and data centers.”
Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.
French telecoms operators Orange, Bouygues and Free have made a €17bn offer to buy most of billionaire Patrick Drahi’s Altice France, in what could be a landmark deal to consolidate the country’s market.
The non binding offer, made on Tuesday, would involve the three operators purchasing the bulk of SFR, the flagship telecoms business of Altice France, which is controlled by Drahi.
The deal would involve SFR’s consumer business — which includes mobile and fixed line broadband customers — being carved up between Bouygues, Free and Orange.
Bouygues and Free would divide the SFR unit providing services to companies between them.
Other Altice France assets, including SFR’s fixed line network and mobile phone spectrum, would be mostly split between the three operators.
The proposed offer has an enterprise value of €17bn, Orange, Bouygues and Iliad-owned Free said.
The split of the assets by value within the deal would be about 43 per cent in favour of Bouygues, 30 per cent for Free and 27 per cent for Orange, they added.
The deal — if accepted by Altice France — is expected to face intense regulatory scrutiny because it would reduce the number of mobile network operators in France from four to three and could prompt concerns about whether consumers will be asked to pay more for services.
Altice France did not immediately respond to a request for comment.
Orange, Bouygues and Free said the offer was conditional on the completion of due diligence, in addition to regulatory approval.
Bouygues group chief executive Olivier Roussat said any deal would take at least 18 months to complete, and would likely close in the second half of 2027.
The agreement — if finalised — would put an end to Drahi’s 11 years of ownership of SFR and greatly reduce his role in the French telecoms market.
Any deal became easier after Drahi closed an agreement with creditors earlier this month to reduce Altice France’s debt level from €24bn to €15.5bn.
The offer by Orange, Bouygues and Free does not include Altice France’s controlling stake in XpFibre, a fixed line network that the Financial Times reported last month was the subject of a separate sales process.
Competition authorities in Brussels have been under pressure to permit more mergers of telecoms companies since a report last year about how to improve EU competitiveness by Mario Draghi, the former European Central Bank president.
Draghi’s report recommended allowing consolidation to create stronger businesses that are better placed to invest in network infrastructure.
AUBURN HILLS, Michigan – Stellantis announced today plans to invest $13 billion over the next four years to grow its business in the critical United States market and to increase its domestic manufacturing footprint. The investment is the largest in the Company’s 100-year U.S. history and will support the introduction of five new vehicles across the brand portfolio in key segments; production of the all-new four-cylinder engine; and the addition of more than 5,000 jobs at plants in Illinois, Ohio, Michigan and Indiana.
The new investment will further expand Stellantis’ already significant U.S. footprint, increasing annual finished vehicle production by 50% over current levels. The new product launches will be in addition to a regular cadence of 19 refreshed products across all U.S. assembly plants and updated powertrains planned through 2029.
“This investment in the U.S. – the single largest in the Company’s history – will drive our growth, strengthen our manufacturing footprint and bring more American jobs to the states we call home,” said Antonio Filosa, Stellantis CEO and North America COO. “As we begin our next 100 years, we are putting the customer at the center of our strategy, expanding our vehicle offerings and giving them the freedom to choose the products they want and love.”
“Accelerating growth in the U.S. has been a top priority since my first day. Success in America is not just good for Stellantis in the U.S. — it makes us stronger everywhere,” Filosa said.
Plant Investment Details(1)
The $13 billion investment plan includes research and development and supplier costs to execute the Company’s full product strategy over the next four years as well as investments in its manufacturing operations. The details of the plant-specific investments follow:
Illinois
Stellantis intends to invest more than $600 million to reopen the Belvidere Assembly Plant to expand production of the Jeep® Cherokee and Jeep Compass for the U.S. market. With an initial production launch expected in 2027, these actions are anticipated to create around 3,300 new jobs.
Ohio
With an investment of nearly $400 million, assembly of an all-new midsize truck, previously allocated to the Belvidere plant, plans to move to the Toledo Assembly Complex, where it will join the Jeep Wrangler and Jeep Gladiator. The production shift could create more than 900 jobs. Launch timing is expected in 2028.
The Company also intends to continue with investments in its Toledo operations as previously announced in January. This includes additional technologies and strong product actions for both the Jeep Wrangler and Jeep Gladiator, and more components critical to production at the Toledo Machining Plant.
Michigan
Stellantis plans to develop an all-new range-extended EV and internal combustion engine large SUV that will be produced at the Warren Truck Assembly Plant beginning in 2028. The Company will invest nearly $100 million to retool the facility. It is anticipated that the new program will add more than 900 jobs at the plant, which currently assembles the Jeep Wagoneer and Grand Wagoneer.
The Company also expects to invest $130 million to prepare the Detroit Assembly Complex– Jefferson for production of the next-generation Dodge Durango, reaffirming its commitment from January. Production is anticipated to launch in 2029.
Indiana
The Company confirms its January announcement to make additional investments in several of its Kokomo facilities to produce the all-new four-cylinder engine – the GMET4 EVO – beginning in 2026. The Company plans to invest more than $100 million and to add more than 100 jobs to ensure that the U.S. will be the manufacturing home of this strategic powertrain.
Stellantis’ U.S. footprint includes 34 manufacturing facilities, parts distribution centers and research and development locations across 14 states. These operations support more than 48,000 employees, 2,600 dealers and nearly 2,300 suppliers in thousands of communities across the country. Today’s announcement builds on the previously announced actions in January 2025.
NOTES
About Stellantis
Stellantis N.V. (NYSE: STLA / Euronext Milan: STLAM / Euronext Paris: STLAP) is a leading global automaker, dedicated to giving its customers the freedom to choose the way they move, embracing the latest technologies and creating value for all its stakeholders. Its unique portfolio of iconic and innovative brands includes Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, FIAT, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall, Free2move and Leasys. For more information, visit www.stellantis.com.
Stellantis Forward-Looking Statements
This communication contains forward-looking statements. In particular, statements regarding future events and anticipated results of operations, business strategies, the anticipated benefits of the proposed transaction, future financial and operating results, the anticipated closing date for the proposed transaction and other anticipated aspects of our operations or operating results are forward-looking statements. These statements may include terms such as “may”, “will”, “expect”, “could”, “should”, “intend”, “estimate”, “anticipate”, “believe”, “remain”, “on track”, “design”, “target”, “objective”, “goal”, “forecast”, “projection”, “outlook”, “prospects”, “plan”, or similar terms. Forward-looking statements are not guarantees of future performance. Rather, they are based on Stellantis’ current state of knowledge, future expectations and projections about future events and are by their nature, subject to inherent risks and uncertainties. They relate to events and depend on circumstances that may or may not occur or exist in the future and, as such, undue reliance should not be placed on them.
Actual results may differ materially from those expressed in forward-looking statements as a result of a variety of factors, including: the ability of Stellantis to launch new products successfully and to maintain vehicle shipment volumes; changes in the global financial markets, general economic environment and changes in demand for automotive products, which is subject to cyclicality; Stellantis’ ability to successfully manage the industry-wide transition from internal combustion engines to full electrification; Stellantis’ ability to offer innovative, attractive products and to develop, manufacture and sell vehicles with advanced features including enhanced electrification, connectivity and autonomous-driving characteristics; Stellantis’ ability to produce or procure electric batteries with competitive performance, cost and at required volumes; Stellantis’ ability to successfully launch new businesses and integrate acquisitions; a significant malfunction, disruption or security breach compromising information technology systems or the electronic control systems contained in Stellantis’ vehicles; exchange rate fluctuations, interest rate changes, credit risk and other market risks; increases in costs, disruptions of supply or shortages of raw materials, parts, components and systems used in Stellantis’ vehicles; changes in local economic and political conditions; changes in trade policy, the imposition of global and regional tariffs or tariffs targeted to the automotive industry, the enactment of tax reforms or other changes in tax laws and regulations; the level of governmental economic incentives available to support the adoption of battery electric vehicles; the impact of increasingly stringent regulations regarding fuel efficiency requirements and reduced greenhouse gas and tailpipe emissions; various types of claims, lawsuits, governmental investigations and other contingencies, including product liability and warranty claims and environmental claims, investigations and lawsuits; material operating expenditures in relation to compliance with environmental, health and safety regulations; the level of competition in the automotive industry, which may increase due to consolidation and new entrants; Stellantis’ ability to attract and retain experienced management and employees; exposure to shortfalls in the funding of Stellantis’ defined benefit pension plans; Stellantis’ ability to provide or arrange for access to adequate financing for dealers and retail customers and associated risks related to the operations of financial services companies; Stellantis’ ability to access funding to execute its business plan; Stellantis’ ability to realize anticipated benefits from joint venture arrangements; disruptions arising from political, social and economic instability; risks associated with Stellantis’ relationships with employees, dealers and suppliers; Stellantis’ ability to maintain effective internal controls over financial reporting; developments in labor and industrial relations and developments in applicable labor laws; earthquakes or other disasters; risks and other items described in Stellantis’ Annual Report on Form 20-F for the year ended December 31, 2024 and Current Reports on Form 6-K and amendments thereto filed with the SEC; and other risks and uncertainties.
Any forward-looking statements contained in this communication speak only as of the date of this document and Stellantis disclaims any obligation to update or revise publicly forward-looking statements. Further information concerning Stellantis and its businesses, including factors that could materially affect Stellantis’ financial results, is included in Stellantis’ reports and filings with the U.S. Securities and Exchange Commission and AFM.
Move will help Walmart stand out as retailers try to win over cautious consumers, one analyst says
A new partnership will let consumers buy items sold at Walmart through OpenAI’s ChatGPT and Instant Checkout.
Walmart Inc. was the Dow Jones Industrial Average’s top percentage gainer on Tuesday and closed at a record high, after the big-box chain announced a partnership that will soon allow customers to buy items at the retailer through OpenAI’s artificial-intelligence chatbot ChatGPT.
Shares of Walmart (WMT) finished 4.9% higher on Tuesday.
The partnership between Walmart and OpenAI will let customers and members buy items sold at Walmart through ChatGPT and Instant Checkout, a shopping tool OpenAI introduced late last month.
“For many years now, e-commerce shopping experiences have consisted of a search bar and a long list of item responses,” Walmart Chief Executive Doug McMillon said in a statement. “That is about to change. There is a native AI experience coming that is multimedia, personalized and contextual.”
Walmart made the announcement as shoppers continue to struggle with higher prices – and increasingly turn to mass retailers for relief – and as retailers navigate the U.S.-led trade war. Meanwhile, concerns have grown about the astronomical costs to develop AI, as well as consumers’ willingness to pay for it.
Walmart already uses AI in things like customer service and clothing design. UBS analyst Michael Lasser, in a note on Tuesday, said Walmart’s announcement underscored the retailer’s ability to keep pace with trends in technology and shopping.
“Thus, this should provide incrementality and differentiation vs. the rest of retail,” he said.
D.A. Davidson’s Michael Baker, in a note on Tuesday, was also upbeat about the move.
“This supports our view that Walmart will be a winner among traditional retailers in the agentic commerce race,” he said, referring to the digital AI “agents” designed to help humans with tasks.
When OpenAI announced Instant Checkout last month, it said U.S. ChatGPT users would be able to make in-chat purchases from domestic Etsy Inc. (ETSY) merchants, with products from sellers on Shopify Inc. (SHOP) to be made available later. At the time, it said shoppers could make single-item purchases on Instant Checkout, with multi-item purchases set to follow.
Shares of Walmart are up 18.7% so far this year.
-Bill Peters
This content was created by MarketWatch, which is operated by Dow Jones & Co. MarketWatch is published independently from Dow Jones Newswires and The Wall Street Journal.
TORONTO, October 14, 2025 – Thomson Reuters (Nasdaq/TSX: TRI), a global content and technology company, today announced a new wave of AI-powered innovations that extend the momentum of CoCounsel Legal. The latest enhancements are headlined by the beta launch of Deep Research on Practical Law expanding the organization’s agentic capabilities and deeper integration with trusted Thomson Reuters content.
In addition, deep product integration between CoCounsel and HighQ has launched, and regional expansion of CoCounsel in French, German and Japanese will be available to customers in October.
Deep Research on Practical Law
Deep Research on Practical Law, currently in beta with select customers, is a significant advancement toward the comprehensive, trusted, and seamless CoCounsel Legal research solution of the future. Deep Research on Practical Law plans the research steps, retrieves the most relevant guidance and templates from Practical Law, and presents clear, supported conclusions. It adapts as follow-up questions are asked, enabling deeper, more nuanced analysis.
This streamlined approach saves time, reduces friction, and builds confidence in the resulting work product. As the leading resource for legal know-how content, Deep Research in Practical Law complements Westlaw’s primary-law expertise and supports the evolving needs of legal professionals. Deep Research on Practical Law will be available in the U.S. in the first half of 2026. CoCounsel Deep Research on both Westlaw and Practical Law will be available in the UK in the same timeframe.
“In this dynamic legal environment, continuous innovation is a necessity, and Thomson Reuters is investing more than $200 million a year organically in AI to develop cutting-edge solutions for our customers,” said Raghu Ramanathan, president, Legal Professionals, Thomson Reuters. “Innovative advancements like Deep Research in Practical Law and key CoCounsel integrations empower legal professionals with professional-grade AI to not only navigate this transformative era, but to thrive in it.”
CoCounsel HighQ Integration
CoCounsel’s generative AI capabilities are now integrated into Thomson Reuters HighQ. With more than 1 million users, HighQ is a secure, collaboration and workflow automation platform trusted by law firms, corporations, government agencies and their clients to work seamlessly on legal services. Through CoCounsel’s advanced AI capabilities, HighQ brings generative AI directly into the collaborative workflow between enterprises, allowing legal teams to provide differentiated, AI-powered services that enhance client experiences, improve operational efficiency and create a competitive advantage.
HighQ Document Insights powered by CoCounsel’s document review and summarize capabilities allows HighQ users to understand documents faster, gain critical insights, and pinpoint and extract information at the point of need.
Users can seamlessly access CoCounsel Drafting to review a document, edit, redline it against a playbook and more. This additional integration allows users to leverage their documents in HighQ and eliminate versioning risks and manual uploads, saving significant time on drafting and review tasks.
Self-Service Q&A delivers a new AI-powered chat experience within modernized HighQ dashboards that allows users to ask natural language questions to curated document sets and receive summarized, highly relevant answers in minutes, transforming static repositories into dynamic knowledge hubs.
Global Expansion
CoCounsel is expanding its footprint internationally adding new languages including French, German, Spanish, Portuguese and Japanese. The professional-grade legal AI assistant will be available in France, Benelux/Brussels, Luxembourg and Quebec (French), Germany, Austria and Switzerland (German), Brazil (Portuguese), Argentina (Spanish), and Japan (Japanese) to meet the needs of legal professionals in those regions. CoCounsel is also available in the U.S., UK, Canada, New Zealand, Hong Kong, Southeast Asia and United Arab Emirates.
Additional functionality has been released across multiple legal solutions and is highlighted via the CoCounsel Monthly Insider for October on the Thomson Reuters Innovation Blog.
In the UK, Thomson Reuters will showcase these innovations to customers at Legal Geek in London from Oct. 15-16. According to Thomson Reuters Future of Professionals research, UK legal professionals predict that AI will enable lawyers to save 3 hours per week which translates to an average of over £12,000 in annual value per lawyer based on our comprehensive study. This leads to over £2billion in estimated annual impact across the UK legal industry.
Thomson Reuters customers will get a preview at the Association of Corporate Counsel Annual Meeting from Oct. 19-22, 2025, as well as Corporates and Legal Professionals Synergy 2025 Conference held in Orlando, Fla. from Nov. 9-12, 2025.
Thomson Reuters
Thomson Reuters (Nasdaq/TSX: TRI) informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. The company serves professionals across legal, tax, accounting, compliance, government, and media. Its products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. For more information, visit tr.com.
As we focus on our goal of achieving net zero emissions in 2030, we also aim to create a common taxonomy for the entire industry to measure carbon emissions.
We’re sharing details on a new methodology we presented at the 2025 OCP regional EMEA summit that leverages AI to improve our understanding of our IT hardware’s Scope 3 emissions.
We are collaborating with the OCP PCR workstream to open source this methodology for the wider industry. This collaboration will be introduced at the 2025 OCP Global Summit.
As Meta focuses on achieving net zero emissions in 2030, understanding the carbon footprint of server hardware is crucial for making informed decisions about sustainable sourcing and design. However, calculating the precise carbon footprint is challenging due to complex supply chains and limited data from suppliers. IT hardware used in our data centers is a significant source of emissions, and the embodied carbon associated with the manufacturing and transportation of this hardware is particularly challenging to quantify.
To address this, we developed a methodology to estimate and track the carbon emissions of hundreds of millions of components in our data centers. This approach involves a combination of cost-based estimates, modeled estimates, and component-specific product carbon footprints (PCFs) to provide a detailed understanding of embodied carbon emissions. These component-level estimates are ranked by the quality of data and aggregated at the server rack level.
By using this approach, we can analyze emissions at multiple levels of granularity, from individual screws to entire rack assemblies. This comprehensive framework allows us to identify high-impact areas for emissions reduction.
Our ultimate goal is to drive the industry to adopt more sustainable manufacturing practices and produce components with reduced emissions. This initiative underscores the importance of high-quality data and collaboration with suppliers to enhance the accuracy of carbon footprint calculations to drive more sustainable practices.
We leveraged AI to help us improve this database and understand our Scope 3 emissions associated with IT hardware by:
Identifying similar components and applying existing PCFs to similar components that lack these carbon estimates.
Extracting data from heterogeneous data sources to be used in parameterized models.
Understanding the carbon footprint of IT racks and applying generative AI (GenAI) as a categorization algorithm to create a new and standard taxonomy. This taxonomy helps us understand the hierarchy and hotspots in our fleet and allows us to provide insights to the data center design team in their language. We hope to iterate on this taxonomy with the data center industry and agree on an industry-wide standard that allows us to compare IT hardware carbon footprints for different types and generations of hardware.
Why We Are Leveraging AI
For this work we used various AI methods to enhance the accuracy and coverage of Scope 3 emission estimates for our IT hardware. Our approach leverages the unique strengths of both natural language processing (NLP) and large language models (LLMs).
NLP For Identifying Similar Components
In our first use case (Identifying similar components with AI), we employed various NLP techniques such as Term Frequency-Inverse Document Frequency (TF-IDF) and Cosine similarity to identify patterns within a bounded, relatively small dataset. Specifically, we applied this method to determine the similarity between different components. This approach allowed us to develop a highly specialized model for this specific task.
LLMs For Handling and Understanding Data
LLMs are pre-trained on a large corpus of text data, enabling them to learn general patterns and relationships in language. They go through a post-training phase to adapt to specific use cases such as chatbots. We apply LLMs, specifically Llama 3.1, in the following three different scenarios:
Unlike the first use case, where we needed a highly specialized model to detect similarities, we opted for LLM for these three use cases because it leverages general human language rules. This includes handling different units for parameters, grouping synonyms into categories, and recognizing varied phrasing or terminology that conveys the same concept. This approach allows us to efficiently handle variability and complexity in language, which would have required significantly more time and effort to achieve using only traditional AI.
Identifying Similar Components With AI
When analyzing inventory components, it’s common for multiple identifiers to represent the same parts or slight variations of them. This can occur due to differences in lifecycle stages, minor compositional variations, or new iterations of the part.
PCFs following the GHG Protocol are the highest quality input data we can reference for each component, as they typically account for the Scope 3 emissions estimates throughout the entire lifecycle of the component. However, conducting a PCF is a time-consuming process that typically takes months. Therefore, when we receive PCF information, it is crucial to ensure that we map all the components correctly.
PCFs are typically tied to a specific identifier, along with aggregated components. For instance, a PCF might be performed specifically for a particular board in a server, but there could be numerous variations of this specific component within an inventory. The complexity increases as the subcomponents of these items are often identical, meaning the potential impact of a PCF can be significantly multiplied across a fleet.
To maximize the utility of a PCF, it is essential to not only identify the primary component and its related subcomponents but also identify all similar parts that a PCF could be applied to. If these similar components are not identified their carbon footprint estimates will remain at a lower data quality. Therefore, identifying similar components is crucial to ensure that we:
Leverage PCF information to ensure the highest data quality for all components.
Maintain consistency within the dataset, ensuring that similar components have the same or closely aligned estimates.
Improve traceability of each component’s carbon footprint estimate for reporting.
To achieve this, we employed a natural language processing (NLP) algorithm, specifically tailored to the language of this dataset, to identify possible proxy components by analyzing textual descriptions and filtering results by component category to ensure relevance.
The algorithm identifies proxy components in two distinct ways:
Leveraging New PCFs: When a new PCF is received, the algorithm uses it as a reference point. It analyzes the description names of components within the same category to identify those with a high percentage of similarity. These similar components can be mapped to a representative proxy PCF, allowing us to use high-quality PCF data in similar components.
Improving Low Data Quality Components: For components with low data quality scores, the algorithm operates in reverse with additional constraints. Starting with a list of low-data-quality components, the algorithm searches for estimates that have a data quality score greater than a certain threshold. These high-quality references can then be used to improve the data quality of the original low-scoring components.
Meta’s Net Zero team reviews the proposed proxies and validates our ability to apply them in our estimates. This approach enhances the accuracy and consistency of component data, ensures that high-quality PCF data is effectively utilized across similar components, and enables us to design our systems to more effectively reduce emissions associated with server hardware.
When PCFs are not available, we aim to avoid using spend-to-carbon methods because they tie sustainability too closely to spending on hardware and can be less accurate due to the influence of factors like supply chain disruptions.
Instead, we have developed a portfolio of methods to estimate the carbon footprint of these components, including through parameterized modeling. To adapt any model at scale, we require two essential elements: a deterministic model to scale the emissions, and a list of data input parameters. For example, we can scale the carbon footprint calculation for a component by knowing its constituent components’ carbon footprint.
However, applying this methodology can be challenging due to inconsistent description data or locations where information is presented. For instance, information about cables may be stored in different tables, formats, or units, so we may be unable to apply models to some components due to difficulty in locating input data.
To overcome this challenge, we have utilized large language models (LLMs) that extract information from heterogeneous sources and inject the extracted information into the parameterized model. This differs from how we apply NLP, as it focuses on extracting information from specific components. Scaling a common model ensures that the estimates provided for these parts are consistent with similar parts from the same family and can inform estimates for missing or misaligned parts.
We applied this approach to two specific categories: memory and cables. The LLM extracts relevant data (e.g., the capacity for memory estimates and length/type of cable for physics-based estimates) and scales the components’ emissions calculations according to the provided formulas.
A Component-Level Breakdown of IT Hardware Emissions Using AI
We utilize our centralized component carbon footprint database not only for reporting emissions, but also to drive our ability to efficiently deploy emissions reduction interventions. Conducting a granular analysis of component-level emissions enables us to pinpoint specific areas for improvement and prioritize our efforts to achieve net zero emissions. For instance, if a particular component is found to have a disproportionately high carbon footprint, we can explore alternative materials or manufacturing processes to mitigate its environmental impact. We may also determine that we should reuse components and extend their useful life by testing or augmenting component reliability. By leveraging data-driven insights at the component level and driving proactive design interventions to reduce component emissions, we can more effectively prioritize sustainability when designing new servers.
We leverage a bill of materials (BOM) to list all of the components in a server rack in a tree structure, with “children” component nodes listed under “parent” nodes. However, each vendor can have a different BOM structure, so two identical racks may be represented differently. This, coupled with the heterogeneity of methods to estimate emissions, makes it challenging to easily identify actions to reduce component emissions.
To address this challenge, we have used AI to categorize the descriptive data of our racks into two hierarchical levels:
Domain-level: A high-level breakdown of a rack into main functional groupings (e.g., compute, network, power, mechanical, and storage)
Component-level: A detailed breakdown that highlights the major components that are responsible for the bulk of Scope 3 emissions (e.g., CPU, GPU, DRAM, Flash, etc.)
We have developed two classification models: one for “domain” mapping, and another for “component” mapping. The difference between these mappings lies in the training data and the additional set of examples provided to each model. We then combine the two classifications to generate a mutually exclusive hierarchy.
During the exploration phase of the new taxonomy generation, we allowed the GenAI model to operate freely to identify potential categories for grouping. After reviewing these potential groupings with our internal hardware experts, we established a fixed list of major components. Once this list was finalized, we switched to using a strict GenAI classifier model as follows:
For each rack, recursively identify the highest contributors, grouping smaller represented items together.
Run a GenAI mutually exclusive classifier algorithm to group the components into the identified categories.
The emissions breakdown for a generic compute rack.
This methodology has been presented at the 2025 OCP regional EMEA summit with the goal to drive the industry toward a common taxonomy for carbon footprint emissions, and open source the methodology we used to create our taxonomy.
These groupings are specifically created to aid carbon footprint analysis, rather than for other purposes such as cost analysis. However, the methodology can be tailored for other purposes as necessary.
Coming Soon: Open Sourcing Our Taxonomies and Methodologies
As we work toward achieving net zero emissions across our value chain in 2030, this component-level breakdown methodology is necessary to help understand our emissions at the server component level. By using a combination of high-quality PCFs, spend-to-carbon data, and a portfolio of methods that leverage AI, we can enhance our data quality and coverage to more effectively deploy emissions reduction interventions.
Our next steps include open sourcing:
The taxonomy and methodology for server rack emissions accounting.
The taxonomy builder using GenAI classifiers.
The aggregation methodology to improve facility reporting processes across the industry.
We are committed to sharing our learnings with the industry as we evolve this methodology, now as part of a collaborative effort with the OCP PCR group.
The revival of the U.S.-China trade war has ended a streak of summer calm that had brought about the lowest volatility since January 2020
The stock market’s “fear gauge” is back above its long-term average.
After one of the quietest summers for the stock market in years, Wall Street’s fear gauge has once again shot higher as investors fret that a trade standoff between the U.S. and China could escalate further.
The Cboe Volatility Index VIX, better known as the VIX, or Wall Street’s “fear gauge,” traded as high as 22.76 on Tuesday, its highest intraday level since May 23, when it traded as high as 25.53, according to Dow Jones Market Data. By the time the market closed, the VIX had moved well off its earlier highs. The index ended the day above 20, a level with some significance.
Since the VIX’s inception in the early 1990s, its long-term average sits just below 20. As a result, investors tend to see this level as the line in the sand between a relatively calm market, and one that is starting to look a bit more panicked.
The level of the VIX is based on trading activity in options contracts tied to the S&P 500 SPX that are due to expire in roughly one month. It is seen as a proxy for how worried traders are about the possibility that stocks could be due for a nosedive. After all, volatility tends to rise more quickly when the market is falling.
A summer lull
Looking back, there were signs that investors were beginning to feel a bit too complacent.
Stocks trundled higher all summer with few interruptions. This placid trading ultimately sent the three-month realized volatility for the S&P 500 to its lowest level since January 2020 last week, according to FactSet data and MarketWatch calculations.
Realized volatility is a calculation that measures how volatile a given index or asset has been in the recent past. The VIX, which measures implied volatility, attempts to gauge how volatile investors expect markets will be in the immediate future.
For a while, the VIX trended lower alongside realized volatility for the S&P 500. But around Labor Day, the two started to diverge.
This could mean a couple of different things, according to portfolio managers who spoke with MarketWatch. The first is that investors increasingly preferred to bet on further upside in the stock market using call options instead of actual shares. Call options on the S&P 500 will deliver a payoff if the index rises above a predetermined level before a given time, which is known as the expiration date.
It might also mean that some traders were scooping up put options, which act like a form of portfolio insurance. Wary of myriad risks that could upset the apple cart following a record-setting rebound earlier in the year, some investors may have preferred to hedge their downside risk, while holding on to their stocks, so as not to miss out on any further gains.
Signs that the market might be bracing for some upcoming turbulence first started to emerge in late September. Between Sept. 29 and Oct. 3, the S&P 500 and the VIX rose simultaneously for five straight sessions. That hadn’t happened since at least 1996, according to an analysis from Carson Group’s Ryan Detrick.
Seeing both the VIX and S&P 500 trend higher hinted that the market’s streak of calm might soon be coming to an end, said Michael Kramer, portfolio manager at Mott Capital Management.
“The tinder was there for something like Friday to occur,” said Mike Thompson, co-portfolio manager at Little Harbor Advisors.
“You just needed that spark to trigger it,” Mott Capital’s Kramer said.
While the U.S.-China trade tensions remain far from settled, Thompson and his brother, Matt Thompson, also a co-portfolio manager at Little Harbor Advisors, are keeping an eye out for any indication that a bigger burst of volatility might lie ahead.
Investors have largely blamed the selloff for the revival of trade tensions between the U.S. and China. On Friday, President Donald Trump threatened 100% tariffs on all Chinese goods imported into the U.S. in retaliation for Beijing stepping up export controls on rare earth metals.
Then on Tuesday, Beijing sanctioned U.S. subsidiaries of a South Korean shipping firm, sparking a global stock-market selloff that had largely reversed by the time the closing bell rang out on Wall Street.
But according to the Thompson brothers, the U.S.-China tariff dance has started to feel a little too familiar for it to be a real cause for concern. Investors appear to be catching on to the pattern of escalation, followed immediately by de-escalation, as each side vies for maximum leverage.
A more plausible threat to market calm, in their view, would be the ructions in the credit market. On Tuesday, JPMorgan Chase & Co. (JPM) Chief Executive Jamie Dimon warned about the potential for more credit problems after the bank lost money on a loan to bankrupt subprime auto lender Tricolor. Trouble in the space could get worse after a long period where conditions in the credit market were relatively favorable.
On Friday, BlackRock (BLK) and other institutional investors asked for their money back from Point Bonita Capital, a fund managed by the investment bank Jefferies (JEF), after the bankruptcy of auto parts supplier First Brands Group saddled the fund with big losses.
“We’re keeping an eye out for whether there is another shoe to drop,” Matt Thompson said.
U.S. stocks were on track to finish mostly higher on Tuesday, until Trump dropped a Truth Social post accusing China of a “Economically Hostile Act” for refusing to purchase soybeans from American farmers. That caused the S&P 500 to finish 0.2% lower, while the Nasdaq Composite COMP ended down 0.8%. Of the three major U.S. indexes, only the Dow Jones Industrial Average DJIA managed to finish higher. Meanwhile, the Russell 2000 RUT, an index of small-cap stocks, quietly notched another record closing high.
-Joseph Adinolfi
This content was created by MarketWatch, which is operated by Dow Jones & Co. MarketWatch is published independently from Dow Jones Newswires and The Wall Street Journal.
We’re presenting Design for Sustainability, a set of technical design principles for new designs of IT hardware to reduce emissions and cost through reuse, extending useful life, and optimizing design.
At Meta, we’ve been able to significantly reduce the carbon footprint of our data centers by integrating several design strategies such as modularity, reuse, retrofitting, dematerialization, using greener materials, and extended hardware lifecycles, Meta can significantly reduce the carbon footprint of its data center infrastructure.
We’re inviting the wider industry to also adopt the strategies outlined here to help reach sustainability goals.
The data centers, server hardware, and global network infrastructure that underpin Meta’s operations are a critical focus to address the environmental impact of our operations. As we develop and deploy the compute capacity and storage racks used in data centers, we are focused on our goal to reach net zero emissions across our value chain in 2030. To do this, we prioritize interventions to reduce emissions associated with this hardware, including collaborating with hardware suppliers to reduce upstream emissions.
What Is Design for Sustainability?
Design for Sustainability is a set of guidelines, developed and proposed by Meta, to aid hardware designers in reducing the environmental impact of IT racks. This considers various factors such as energy efficiency and the selection, reduction, circularity, and end-of-life disposal of materials used in hardware. Sustainable hardware design requires collaboration between hardware designers, engineers, and sustainability experts to create hardware that meets performance requirements while limiting environmental impact.
In this guide, we specifically focus on the design of racks that power our data centers and offer alternatives for various components (e.g., mechanicals, cooling, compute, storage and cabling) that can help rack designers make sustainable choices early in the product’s lifecycle.
Our Focus on Scope 3 Emissions
To reach our net zero goal, we are primarily focused on reducing our Scope 3 (or value chain) emissions from physical sources like data center construction and our IT hardware (compute, storage and cooling equipment) and network fiber infrastructure.
While the energy efficiency of the hardware itself deployed in our data centers helps reduce energy consumption, we have to also consider IT hardware emissions associated with the manufacturing and delivery of equipment to Meta, as well as the end-of-life disposal, recycling, or resale of this hardware.
Our methods for controlling and reducing Scope 3 emissions generally involve optimizing material selection, choosing and developing lower carbon alternatives in design, and helping to reduce the upstream emissions of our suppliers.
For internal teams focused on hardware, this involves:
Optimizing hardware design for the lowest possible emissions, extending the useful life of materials as much as possible with each system design, or using lower carbon materials.
Being more efficient by extending the useful life of IT racks to potentially skip new generations of equipment.
Harvesting server components that are no longer available to be used as spares. When racks reach their end-of-life, some of the components still have service life left in them and can be harvested and reused in a variety of ways. Circularity programs harvest components such as dual In-line memory modules (DIMMs) from end-of-life racks and redeploy them in new builds.
Knowing the emissions profiles of suppliers, components, and system designs. This in turn informs future roadmaps that will further reduce emissions.
Collaborating with suppliers to electrify their manufacturing processes, to transition to renewable energy, and to leverage lower carbon materials and designs.
These actions to reduce Scope 3 emissions from our IT hardware also have the additional benefit of reducing the amount of electronic waste (e-waste) generated from our data centers.
An Overview of the Types of Racks We Deploy
There are many different rack designs deployed within Meta’s data centers to support different workloads and infrastructure needs, mainly:
AI – AI training and inference workloads
Compute – General compute needed for running Meta’s products and services
Storage – Storing and maintaining data used by our products
Network – Providing Low-latency interconnections between servers
While there are differences in architecture across these different rack types, most of these racks apply general hardware design principles and contain active and passive components from a similar group of suppliers. As such, the same design principles for sustainability apply across these varied rack types.
Within each rack, there are five main categories of components that are targeted for emissions reductions:
Compute (i.e., memory, HDD/SSD)
Storage
Network
Power
Rack infrastructure (i.e., mechanical and thermals)
The emissions breakdown for a generic compute rack is shown below.
Our Techniques for Reducing Emissions
We focus on four main categories to address emissions associated with these hardware components:
We will cover a few of the levers listed above in detail below.
Modular Rack Designs
Modular Design which allows older rack components to be re-used in newer racks. Open Rack designs (ORv2 & ORv3) form the bulk of high volume racks that exist in our data centers.
Here are some key aspects of the ORv3 modular rack design:
ORv3 separates Power Supply Units (PSUs) and Battery Backup Units (BBUs) into their own shelves. This allows for more reliable and flexible configurations, making repairs and replacements easier as each field replaceable unit (FRU) is toolless to replace.
Power and flexibility The ORv3 design includes a 48 V power output, which allows the power shelf to be placed anywhere in the rack. This is an improvement over the previous ORV2 design, which limited the power shelf to a specific power zone
Configurations The rack can accommodate different configurations of PSU and BBU shelves to meet various platform and regional requirements. For example, North America uses a dual AC input per PSU shelf, while Europe and Asia use a single AC input.
Commonization effort There is an ongoing effort to design a “commonized” ORv3 rack frame that incorporates features from various rack variations into one standard frame. This aims to streamline the assembly process, reduce quality risks, and lower overall product costs
ORv3N A derivative of ORv3, known as ORv3N, is designed for network-specific applications. It includes in-rack PSU and BBU, offering efficiency and cost improvements over traditional in-row UPS systems
These design principles should continue to be followed in successive generations of racks. With the expansion of AI workloads, new specialized racks for compute, storage, power and cooling are being developed that are challenging designers to adopt the most modular design principles.
Re-Using/Retrofitting Existing Rack Designs
Retrofitting existing rack designs for new uses/high density is a cost-effective and sustainable approach to meet evolving data center needs. This strategy can help reduce e-waste, lower costs, and accelerate deployment times. Benefits of re-use/retrofitting include:
Cost savings Retrofitting existing racks can be significantly cheaper compared to purchasing new racks.
Reduced e-waste Reusing existing racks reduces the amount of e-waste generated by data centers.
Faster deployment Retrofitting existing racks can be completed faster than deploying new racks, as it eliminates the need for procurement and manufacturing lead times.
Environmental benefits Reducing e-waste and reusing existing materials helps minimize the environmental impact of data centers.
There are several challenges when considering re-using or retrofitting racks:
Compatibility issues Ensuring compatibility between old and new components can be challenging.
Power and cooling requirements Retrofitting existing racks may require upgrades to power and cooling systems to support new equipment.
Scalability and flexibility Retrofitting existing racks may limit scalability and flexibility in terms of future upgrades or changes.
Testing and validation Thorough testing and validation are required to ensure that retrofitted racks meet performance and reliability standards.
Overall, the benefits of retrofitting existing racks are substantial and should be examined in every new rack design.
Green Steel
Steel is a significant portion of a rack and chassis and substituting traditional steel with green steel can reduce emissions. Green steel is typically produced using electric arc furnaces (EAF) instead of traditional basic oxygen furnaces (BOF), allowing for the use of clean and renewable electricity and a higher quantity of recycled content. This approach significantly reduces carbon emissions associated with steel production. Meta collaborates with suppliers who offer green steel produced with 100% clean and renewable energy.
Recycled Steel, Aluminum, and Copper
While steel is a significant component of rack and chassis, aluminum and copper are extensively used in heat sinks and wiring. Recycling steel, aluminum, and copper saves significant energy needed to produce hardware from raw materials.
As part of our commitment to sustainability, we now require all racks/chassis to contain a minimum of 20% recycled steel. Additionally, all heat sinks must be manufactured entirely from recycled aluminum or copper. These mandates are an important step in our ongoing sustainability journey.
Several of our steel suppliers, such as Tata Steel, provide recycled steel. Product design teams may ask their original design manufacturer (ODM) partners to make sure that recycled steel is included in the steel vendor(s) selected by Meta’s ODM partners. Similarly, there are many vendors that are providing recycled aluminum and copper products.
Improving Reliability to Extend Useful Life
Extending the useful life of racks, servers, memory, and SSDs helps Meta reduce the number of hardware equipment that needs to be ordered. This has helped achieve significant reductions in both emissions and costs.
A key requirement for extending useful life of hardware is the reliability of the hardware component or rack. Benchmarking reliability is an important element to determine whether hardware life extensions are feasible and for how long. Additional consideration needs to be given to the fact that spares and vendor support may have diminishing availability. Also, extending hardware life also comes with the risk of increased equipment failure, so a clear strategy to deal with the higher incidence of potential failure should be put in place.
Dematerialization
Dematerialization and removal of unnecessary hardware components can lead to a significant reduction in the use of raw materials, water, and/or energy. This entails reducing the use of raw materials such as steel on racks or removing unnecessary components on server motherboards while maintaining the design constraints established for the rack and its components.
Dematerialization also involves consolidating multiple racks into fewer, more efficient ones, reducing their overall physical footprint.
Extra components on hardware boards are included for several reasons:
Future-proofing Components might be added to a circuit board in anticipation of future upgrades or changes in the design. This allows manufacturers to easily modify the board without having to redesign it from scratch.
Flexibility Extra components can provide flexibility in terms of configuration options. For example, a board might have multiple connectors or interfaces that can be used depending on the specific application.
Debugging and testing Additional components can be used for debugging and testing purposes. These components might include test points, debug headers, or other features that help engineers diagnose issues during development.
Redundancy In some cases, extra components are included to provide redundancy in case one component fails. This is particularly important in high-reliability applications where system failure could have significant consequences.
Modularity Extra components can make a board more modular, allowing users to customize or upgrade their system by adding or removing modules.
Regulatory compliance Some components might be required for regulatory compliance, such as safety features or electromagnetic interference (EMI) filtering.
In addition, changes in requirements over time can also lead to extra components. While it is very difficult to modify systems in production, it is important to make sure that each hardware design optimizes for components that will be populated.
Examples of extra components on hardware boards include:
Unpopulated integrated circuit (IC) sockets or footprints
Unused connectors or headers
Test points or debug headers
Redundant power supplies or capacitors
Optional memory or storage components
Unconnected or reserved pins on ICs
In addition to hardware boards, excess components may also be present in other parts of the rack. Removing excess components can lead to lowering the emissions footprint of a circuit board or rack.
Productionizing New Technologies With Lower Emissions
Productionizing new technologies can help Meta significantly reduce emissions. Memory and SSD/HDD are typically the single largest source of embodied carbon emissions in a server rack. New technologies can help Meta reduce emissions and costs while providing a substantially higher power-normalized performance.
Examples of such technologies include:
Transitioning to SSD from HDD can reduce emissions by requiring fewer drives, servers, racks, BBUs, and PSUs, as well as help reduce overall energy usage.
Depending on local environmental conditions, and the data center’s workload, using liquid cooling in server racks can be up to 17% more carbon-efficient than traditional air cooling.
Source: OCP Global Summit, Oct 15-17, 2024, San Jose, CA.
Teams can explore additional approaches to reduce emissions associated with memory/SSD/HDD which include:
Alternate technologies such as phase-change memory (PCM) or Magnetoresistive Random-Access Memory (MRAM) that have the same performance with low carbon.
Use Low-Power Double Data Rates (LPDDRs ) for low power consumption and high bandwidth instead of DDR.
Removing/reusing unused memory modules to reduce energy usage or down-clocking them during idle periods.
Using fewer high capacity memory modules to reduce power and cooling needs. Use High Bandwidth Memory (HBM) which uses much less energy than the DDR memory.
Choosing the Right Suppliers
Meta engages with suppliers to reduce emissions through its net zero supplier engagement program. This program is designed to set GHG reduction targets with selected suppliers to help achieve our net zero target. Key aspects of the program include:
Providing capacity building: Training suppliers on how to measure emissions, set science-aligned targets, build reduction roadmaps, procure renewable energy, and understand energy markets.
Scaling up: In 2021 the program started with 39 key suppliers; by 2024 it expanded to include 183 suppliers, who together account for over half of Meta’s supplier-related emissions.
Setting target goals: Meta aims to have two-thirds of its suppliers set science-aligned greenhouse gas reduction targets by 2026 . As of end-2024, 48% (by emissions contribution) have done so.
The Clean Energy Procurement Academy (CEPA), launched in 2023 (with Meta and other corporations), helps suppliers — especially in the Asia-Pacific region — learn how to procure renewable energy via region-specific curricula.
The Road to Net Zero Emissions
The Design for Sustainability principles outlined in this guide represent an important step forward in Meta’s goal to achieve net zero emissions in 2030. By integrating innovative design strategies such as modularity, reuse, retrofitting, and dematerialization, alongside the adoption of greener materials and extended hardware lifecycles, Meta can significantly reduce the carbon footprint of its data center infrastructure. These approaches not only lower emissions but also drive cost savings, e-waste reductions, and operational efficiency, reinforcing sustainability as a core business value.
Collaboration across hardware designers, engineers, suppliers, and sustainability experts is essential to realize these goals. The ongoing engagement with suppliers further amplifies the impact by addressing emissions across our entire value chain. As Meta continues to evolve its rack designs and operational frameworks, the focus on sustainability will remain paramount, ensuring that future infrastructure innovations support both environmental responsibility and business performance.
Ultimately, the success of these efforts will be measured by tangible emissions reductions, extended useful life of server hardware, and the widespread adoption of low carbon technologies and materials.
ENGLEWOOD, Colo.–(BUSINESS WIRE)–
Liberty Media Corporation (“Liberty Media”) (Nasdaq: FWONA, FWONK, LLYVA, LLYVK) will hold a virtual special meeting of its Series A Liberty Live common stock (“LLYVA”) and Series B Liberty Live common stock (“LLYVB”) holders on Friday, December 5, 2025 at 8:30 a.m. Mountain time. At the special meeting, such stockholders will be asked to consider and vote on a proposal related to Liberty Media’s proposed transaction to separate the Liberty Live Group by means of a redemptive split-off (the “Split-Off”) into a separate public company, Liberty Live Holdings, Inc. (“SplitCo”).
Prior to the completion of the Split-Off, certain assets and liabilities will be reattributed between the Formula One Group and the Liberty Live Group (the “Reattribution”). Additional information regarding the values of the assets and liabilities included in the Reattribution will be provided via press release in connection with the closing of the Split-Off.
Information regarding the Split-Off and matters on which holders of LLYVA and LLYVB are being asked to vote will be available in the definitive proxy materials to be filed by Liberty Media with respect to the special meeting, which are expected to be filed November 4, 2025. Assuming satisfaction of all conditions to closing, the Split-Off is expected to be completed as soon as practicable following the stockholder vote, and we currently expect closing to occur on December 15, 2025.
Additional Special Meeting Details
The special meeting will be held via the Internet and will be a completely virtual meeting of stockholders. LLYVA and LLYVB stockholders of record as of the record date for the special meeting will be able to listen, vote and submit questions pertaining to the special meeting of stockholders by visiting www.virtualshareholdermeeting.com/LMC2025SM. The record date for the special meeting is 5:00 p.m., New York City time, on Thursday, October 9, 2025. Stockholders will need the 16-digit control number that is printed in the box marked by the arrow on the stockholder’s proxy card for the special meeting to enter the virtual special meeting website. A technical support number will become available at the virtual meeting link 10 minutes prior to the scheduled meeting time.
In addition, access to the special meeting will be available on the Liberty Media website. All interested persons should visit https://www.libertymedia.com/investors/news-events/ir-calendar to access the webcast. An archive of the webcast will also be available on this website after appropriate filings have been made with the SEC.
About Liberty Media Corporation
Liberty Media Corporation operates and owns interests in media, sports and entertainment businesses. Those businesses are attributed to two tracking stock groups: the Formula One Group and the Liberty Live Group. The businesses and assets attributed to the Formula One Group (NASDAQ: FWONA, FWONK) include Liberty Media’s subsidiaries Formula 1, MotoGP, Quint and other minority investments. The businesses and assets attributed to the Liberty Live Group (NASDAQ: LLYVA, LLYVK) include Liberty Media’s interest in Live Nation and other minority investments.
Forward-Looking Statements
This communication includes certain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including certain statements relating to the Split-Off and Liberty Media’s definitive proxy statement for the special meeting and other matters that are not historical facts. All statements other than statements of historical fact are “forward-looking statements” for purposes of federal and state securities laws. These forward-looking statements generally can be identified by phrases such as “possible,” “potential,” “intends” or “expects” or other words or phrases of similar import or future or conditional verbs such as “will,” “may,” “might,” “should,” “would,” “could,” or similar variations. These forward-looking statements involve many risks and uncertainties that could cause actual results to differ materially from those expressed or implied by such statements, including, without limitation, the satisfaction of conditions to the Split-Off. These forward-looking statements speak only as of the date of this communication, and Liberty Media expressly disclaims any obligation or undertaking to disseminate any updates or revisions to any forward-looking statement contained herein to reflect any change in Liberty Media’s expectations with regard thereto or any change in events, conditions or circumstances on which any such statement is based. Please refer to the publicly filed documents of Liberty Media, including its most recent Forms 10-K and 10-Q, as such risk factors may be amended, supplemented or superseded from time to time by other reports Liberty Media subsequently files with the SEC, for additional information about Liberty Media and about the risks and uncertainties related to Liberty Media’s business which may affect the statements made in this communication.
Additional Information
Nothing in this press release shall constitute a solicitation to buy or an offer to sell shares of common stock of Liberty Media or SplitCo. The proposed offer and issuance of shares of SplitCo common stock in the Split-Off will be made only pursuant to an effective registration statement on Form S-4, including a proxy statement and a notice of meeting and action of Liberty Media and prospectus of SplitCo. LIBERTY MEDIA STOCKHOLDERS AND OTHER INVESTORS ARE URGED TO READ THE REGISTRATION STATEMENT, TOGETHER WITH ALL RELEVANT SEC FILINGS REGARDING THE PROPOSED TRANSACTION, AND ANY OTHER RELEVANT DOCUMENTS FILED AS EXHIBITS THEREWITH, AS WELL AS ANY AMENDMENTS OR SUPPLEMENTS TO THOSE DOCUMENTS, BECAUSE THEY WILL CONTAIN IMPORTANT INFORMATION ABOUT THE PROPOSED TRANSACTION. After the registration is declared effective, the proxy statement/notice/prospectus and other relevant materials for the proposed transaction will be mailed to all holders of Liberty Media’s LLYVA and LLYVB common stock. Copies of these SEC filings will be available, free of charge, at the SEC’s website (http://www.sec.gov). Copies of the filings together with the materials incorporated by reference therein will also be available, without charge, by directing a request to Liberty Media Corporation, 12300 Liberty Boulevard, Englewood, Colorado 80112, Attention: Investor Relations, Telephone: (877) 772-1518.
Participants in a Solicitation
Liberty Media anticipates that the following individuals will be participants (the “Liberty Media Participants”) in the solicitation of proxies from holders of Liberty Media’s LLYVA and LLYVB common stock in connection with the proposed transaction: John C. Malone, Chairman of the Liberty Media Board of Directors, Robert R. Bennett, Chase Carey, Brian M. Deevy, M. Ian G. Gilchrist, Evan D. Malone, Larry E. Romrell, and Andrea L. Wong, all of whom are members of the Liberty Media Board of Directors, and Derek Chang, Liberty Media’s President and Chief Executive Officer and a member of the Liberty Media Board of Directors, Brian J. Wendling, Liberty Media’s Chief Accounting Officer and Principal Financial Officer, and Renee L. Wilm, Liberty Media’s Chief Legal Officer and Chief Administrative Officer. Information regarding the Liberty Media Participants, including a description of their direct or indirect interests, by security holdings or otherwise, can be found under the caption “Security Ownership of Certain Beneficial Owners and Management—Security Ownership of Management” contained in Liberty Media’s proxy statement on Schedule 14A (the “Proxy Statement”), which was filed with the SEC on March 28, 2025 and is available at: https://www.sec.gov/ix?doc=/Archives/edgar/data/0001560385/000110465925029081/tm252442-2_def14a.htm. To the extent that certain Liberty Media Participants or their affiliates have acquired or disposed of security holdings since the “as of” date disclosed in the Proxy Statement, such transactions have been or will be reflected on Statements of Change in Ownership on Form 4 or amendments to beneficial ownership reports on Schedules 13D filed with the SEC, which are available at: https://www.sec.gov/edgar/browse/?CIK=1560385&owner=exclude. Additional information regarding the Liberty Media Participants in the proxy solicitation and a description of their interests is contained in the proxy statement for Liberty Media’s special meeting of stockholders and other relevant materials filed with the SEC in respect of the Split-Off. These documents can be obtained free of charge from the sources indicated above.
View source version on businesswire.com: https://www.businesswire.com/news/home/20251014514078/en/
