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Videotron Ltd. Prices Private Offering of $600 Million Series 1 Senior Notes due 2029 and $400 Million Series 2 Senior Notes due 2034

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MONTRÉAL, June 14, 2024 /CNW/ – Videotron Ltd. (“Videotron”) today announced the pricing of its $600 million aggregate principal amount of 4.650% Series 1 Senior Notes due July 15, 2029 (the “Series 1 Notes”) and $400 million aggregate principal amount of 5.000% Series 2 Senior Notes due July 15, 2034 (the “Series 2 Notes” and, together with the Series 1 Notes, the “Notes”) (this offering, the “Offering”). The Series 1 Notes will be sold at $999.47 per $1,000 principal amount of Series 1 Notes and the Series 2 Notes will be sold at $996.75 per $1,000 principal amount of Series 2 Notes. Videotron intends to use the net proceeds of this Offering to repay existing indebtedness, which may include a portion of the revolving facility drawings under Videotron’s credit agreement and repayment of a portion of Videotron’s existing notes. The Offering is expected to close on or about June 21, 2024, subject to customary closing conditions. 

“Shortly after obtaining an investment grade rating from S&P Global Ratings and Moody’s Ratings, I am very proud to announce that Videotron has just priced its first issuance of investment grade notes”, said Pierre Karl Péladeau, President and Chief Executive Officer of Quebecor. “The great success of this transaction demonstrates the financial markets’ trust in Videotron and marks a major step in reducing its borrowing costs,” he added.

This news release shall not constitute an offer to sell or the solicitation of an offer to sell or the solicitation of an offer to buy any securities, nor shall there be any sale of securities in any jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such jurisdiction.

The Notes are being offered in Canada on a private placement basis in reliance upon exemptions from the prospectus requirements under applicable securities legislation. The Notes have not been and will not be qualified for sale to the public under applicable securities laws in Canada and, accordingly, any offer and sale of the Notes in Canada will be made on a basis which is exempt from the prospectus requirements of such securities laws. The Notes and the related guarantees have not been and will not be registered under the United States Securities Act of 1933 or applicable state securities laws, and the Notes may not be offered or sold in the United States absent registration or an applicable exemption from registration. The Notes have not been and will not be qualified for sale to the public under applicable Canadian securities laws and, accordingly, any offer and sale of the Notes in Canada will be made on a basis which is exempt from the prospectus and dealer registration requirements of such securities laws.

Videotron (www.videotron.com), a wholly owned subsidiary of Quebecor Media Inc. (www.quebecor.com), is an integrated communications company engaged in television, entertainment, Internet access, wireline telephone and mobile telephone services.

Forward‑Looking Statements

This news release contains “forward-looking information” within the meaning of applicable Canadian securities legislation and “forward-looking statements” within the meaning of United States federal securities legislation (collectively, “forward-looking statements”). All statements other than statements of historical facts included in this press release, including statements regarding the prospects of our industry and our prospects, plans, financial position and business strategy, may constitute forward-looking statements. These forward-looking statements are based on current expectations, estimates, forecasts and projections about the industries in which we operate as well as beliefs and assumptions made by our management. Such statements include, in particular, statements about our plans, prospects, financial position and business strategies. Words such as “may,” “will,” “expect,” “continue,” “intend,” “estimate,” “anticipate,” “plan,” “foresee,” “believe,” or “seek,” or the negatives of these terms or variations of them or similar terminology, are intended to identify such forward-looking statements. Although we believe that the expectations reflected in those forward-looking statements are reasonable, these statements, by their nature, involve risks and uncertainties and are not guarantees of future performance. Such statements are also subject to assumptions concerning, among other things: our anticipated business strategies; anticipated trends in our business; anticipated reorganizations of any of our segments or businesses, and any related restructuring provisions or impairment charges; and our ability to continue to control costs. We can give no assurance that these estimates and expectations will prove to have been correct. Actual outcomes and results may, and often do, differ from what is expressed, implied or projected in such forward-looking statements, and such differences may be material. Some important factors that could cause actual results to differ materially from those expressed in these forward-looking statements include, but are not limited to: our ability to successfully continue developing our network and facilities-based mobile services; general economic, financial or market conditions and variations in our businesses; the intensity of competitive activity in the industries in which we operate; new technologies that might change consumer behaviour toward our product suite; unanticipated higher capital spending required to develop our network or to address the continued development of competitive alternative technologies, or the inability to obtain additional capital to continue the development of our business; our ability to implement successfully our business and operating strategies and manage our growth and expansion; risks relating to the acquisition of Freedom Mobile Inc. (“Freedom”), including our ability to successfully integrate Freedom’s operations and to realize synergies, and potential unknown liabilities or costs associated with the acquisition of Freedom; the anticipated benefits and effects of the acquisition of Freedom, which may not be realized in a timely manner or at all, and ongoing operating costs and capital expenditures, which could be different than anticipated, as well as unanticipated litigation or other regulatory proceedings associated with the acquisition of Freedom, which could result in changes to the parameters of the transaction; the impacts of the significant and recurring investments that will be required in our new Freedom, Videotron mobile virtual network operator and other markets for development and expansion and to compete effectively with the incumbent local exchange carriers and other current or potential competitors in these markets, including the fact that the post acquisition our business will continue to face the same risks that we currently face, but will also face increased risks relating to new geographies and markets; disruptions to the network through which we provide our digital television, Internet access, mobile and wireline telephony and over-the-top video services, and our ability to protect such services from piracy, unauthorized access or other security breaches; labour disputes or strikes; service interruptions resulting from equipment breakdown, network failure, the threat of natural disasters, epidemics, pandemics and other public health crises and political instability in some countries;  the impact of emergency measures implemented by various levels of government; changes in our ability to obtain services and equipment critical to our operations; changes in laws and regulations, or in their interpretations, which could result, among other things, in the loss (or reduction in value) of our licenses or markets or in an increase in competition, compliance costs or capital expenditures; our substantial indebtedness, the tightening of credit markets, and the restrictions on our business imposed by the terms of our debt; and interest rate fluctuations that affect a portion of our interest payment requirements on long-term debt. We caution you that the above list of cautionary statements is not exhaustive. These and other factors could cause actual results to differ materially from our expectations expressed in the forward-looking statements included in this press release, and you are encouraged to read “Item 3. Key Information – Risk Factors” as well as statements located elsewhere in Videotron’s annual report on Form 20-F for the year ended December 31, 2023, and Videotron’s Quarterly Report under Form 6-K for the three-month period ended March 31, 2024, including Management’s Discussion and Analysis and unaudited interim condensed consolidated financial statements included therein for further details and descriptions of these and other factors. Each of these forward-looking statements speaks only as of the date of this press release. We will not update these statements unless applicable securities laws require us to do so.

SOURCE Videotron Ltd.

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BinBase Expands 2026 BIN Dataset with Instant Payout Intelligence for iGaming, Gambling, and Cross-Border Transfers

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BinBase updates its 2026 dataset with specialized Fast Funds, Visa Direct, and Mastercard MoneySend indicators to help iGaming operators and payout platforms execute seamless, instant card disbursements.

MIAMI, July 23, 2026 /PRNewswire-PRWeb/ — BinBase, a global provider of payment routing intelligence and card issuing data, has introduced specialized instant payout indicators as part of its upgraded 2026 BIN Database. Tailored for iGaming operators, online gambling platforms, crypto-to-fiat ramps, and payout aggregators, the updated dataset helps platform engineers streamline real-time card disbursements and Push-to-Card (P2C) transactions.

In high-velocity sectors such as online betting and gaming, instantaneous player payouts are a primary driver of customer retention. However, executing Push-to-Card transactions through protocols like Visa Direct and Mastercard MoneySend requires knowing whether the receiving card issuer supports Fast Funds for specific merchant category codes (MCCs). Attempting instant payouts on non-eligible cards leads to declined transactions, elevated processing fees, and poor user experiences.

The 2026 BinBase release solves this operational bottleneck by delivering dedicated attributes for real-time fund disbursements:

Fast Funds Eligibility: Granular indicators identifying domestic and cross-border Fast Funds support across global Visa and Mastercard ranges.Online Gambling Fast Funds (OG FF): Dedicated flags specifically identifying card ranges authorized to receive real-time gambling and betting payouts.Mastercard MoneySend & Visa Direct Indicators: Precise protocol compatibility markers (MS Ind & MT Ind) ensuring push transactions are routed only to eligible recipient cards.Direct Debit & Pull-Funds Support: Indicators for recurring collections and account-funding transactions.

“Player payouts in iGaming cannot wait for standard 2-to-3-day ACH settlements,” said a spokesperson for Damiko Inc. “By embedding our Fast Funds and Gambling FF flags into their payment engines, operators can instantly validate recipient cards before initiating a transfer, guaranteeing high success rates and instant liquidity for their users.”

Fintech engineers and payout architects can examine the full 29-field database schema and access a free 2026 sample dataset on GitHub.

To explore commercial licensing, bulk database downloads, or custom data feeds, visit BinBase at https://binbase.com.

About Damiko Inc

Damiko Inc is a US-based fintech data provider specializing in card issuer analytics, payment routing data, and global BIN database solutions. Operating through its flagship product, BinBase.com, the company supplies high-precision transaction intelligence to help merchants and payment facilitators worldwide optimize approval rates and mitigate processing fees.

Media Contact
Fedor Lavrikoff, BinBase, 1 7866133334, sales@binbase.com, www.binbase.com 

View original content:https://www.prweb.com/releases/binbase-expands-2026-bin-dataset-with-instant-payout-intelligence-for-igaming-gambling-and-cross-border-transfers-302829344.html

SOURCE BinBase

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Walnut Coding’s Young Coders Serve as ‘Instructors’ at Huawei Cloud Developer Training Camp

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Ages 8 and 15, students showcase AI-era project-building skills from concept to working application

BEIJING, July 23, 2026 /PRNewswire/ — Walnut Coding (the “Company”), a leading online platform for youth coding education, said two of its students – ages 8 and 15 – have joined the “instructor” lineup at Huawei Cloud Developer Training Camp, making them among the youngest “instructors” in the program’s history. The Company cites the pair as a prime example of how young learners can combine coding fundamentals with AI tools to turn ideas into working applications.

The two students, Bolin Du, 8, and Peiqi Gao, 15, built working applications using Huawei Cloud CodeArts, an AI coding assistant, then presented the projects to the training camp themselves – walking the audience through their design choices, technical builds, and debugging process.

The move lands at a moment when AI coding tools are forcing a rethink across the education sector. Tools that can generate functioning code from a plain-language prompt have undercut the traditional argument for teaching children to program – that they need the skill to build things themselves. Walnut Coding’s answer is that the more valuable skill now is judgment – knowing what problem to solve, breaking it into parts, and determining whether an AI’s output actually works.

Gao built a travel-planning application that generates routes, itineraries, and recommendations based on user input, handling the project end to end, from requirements and design through coding and debugging. Du, the younger of the two, built an interactive calendar application, using HTML for page structure, CSS for visual design, and JavaScript for interactive features. Both students then took on an instructor’s role at the camp, presenting their project goals and technical implementation to the audience – a step Walnut Coding says separated the work from a typical classroom assignment.

These were not classroom exercises but working projects, built and presented inside a professional developer-training environment. The experience demanded more from both students than simply producing something functional – they needed to articulate their reasoning, defend technical choices, and refine the final result under scrutiny. Their participation signals a broader shift underway in what youth coding education can deliver.

AI is making code generation easier, but it is also redrawing which skills actually matter. A student who relies only on one-click generation may get a rough prototype quickly, but still struggle to spot logical flaws, judge whether the output is reliable, or turn an abstract idea into a product that actually works. Students with programming foundations, by contrast, are better positioned to define requirements, evaluate what the AI produces, correct its errors, and treat the technology as a tool rather than a shortcut to lean on.

“AI can help children generate code faster, but it cannot decide for them what problem they should solve, nor can it make the final judgment about whether the result is truly effective,” said Pengxuan Zeng, founder and CEO of Walnut Coding. “What these two students demonstrated is not just coding technique, but the ability to define needs, break down tasks, verify outcomes, and turn an idea into a working product. That is why we believe young people still need to learn programming in the AI era.”

Walnut Coding structures its courses around that thesis, pairing student-led project work with teaching-assistant guidance and AI-assisted support. According to the Company, this data is continuously fed back into its systems to refine the personalization of AI-assisted feedback — a closed-loop process linking teaching, practice, feedback, and curriculum development.

The Company frames the payoffs less around producing professional software engineers than around a broader form of literacy. As AI continues to reshape how tasks get done, the ability to understand the technology, structure problems clearly and collaborate effectively with intelligent tools may prove one of the most durable skills a young learner can develop.

Walnut Coding says it plans to keep expanding opportunities for students to build practical projects, partner with industry technology platforms such as Huawei Cloud, and develop the core capabilities needed to build with technology in the AI era.

View original content:https://www.prnewswire.com/news-releases/walnut-codings-young-coders-serve-as-instructors-at-huawei-cloud-developer-training-camp-302833884.html

SOURCE Walnut Coding

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MOREH Showcases High-Performance LLM Inference on AMD GPUs at AMD Advancing AI 2026

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SAN FRANCISCO, July 23, 2026 /PRNewswire/ — Moreh, an AI infrastructure software company, led by CEO Gangwon Jo, participated in AMD Advancing AI 2026, AMD’s flagship annual AI event held in San Francisco on July 22–23 (local time), where it demonstrated its distributed inference solution, the MoAI Inference Framework, running on AMD GPUs.

At the event, Moreh presented a live demonstration of the GLM-5.1 large language model (LLM) powered by the MoAI Inference Framework on a system equipped with 32 AMD Instinct™ MI300X GPUs across four nodes. Visitors experienced the chatbot firsthand, evaluating its response speed and service quality while observing performance across a range of real-world use cases.

Unlike conventional demonstrations that simply run an AI model, Moreh’s showcase displayed key inference service metrics in real time, including GPU utilization, Tokens Per Second (TPS), Time To First Token (TTFT), and Time Per Output Token (TPOT). This enabled attendees to directly verify both inference performance and GPU resource efficiency in a production-like service environment.

Global AI industry leaders and enterprise customers attending the event expressed strong interest in the system’s fast response times and stable performance. In particular, the live deployment of the computationally demanding GLM-5.1 model on AMD GPUs at production-grade service levels received positive feedback from visitors.

Moreh’s MoAI Inference Framework is widely recognized as the world’s first commercially deployed distributed inference solution built for the AMD ecosystem. Its distributed inference and heterogeneous computing technologies are designed to dramatically reduce AI service costs, enabling broader adoption of AI worldwide. The technology addresses one of the industry’s biggest challenges-the rapidly rising infrastructure and service costs caused by increasingly larger AI models-by delivering a more efficient inference infrastructure.

Moreh CEO Gangwon Jo stated, “This event provided an opportunity for global customers to verify firsthand that top-tier inference performance can be achieved on AMD GPU environments,” and added “We will continue advancing our AI infrastructure software so enterprises can operate AI services as efficiently as possible, regardless of the underlying GPU platform.”

Moreh develops its own AI infrastructure engine and has expanded its end-to-end AI capabilities through its foundation LLM subsidiary, Motif Technologies, covering both AI infrastructure and foundation models. The company is also strengthening its presence in the global AI market through strategic partnerships with leading technology companies, including AMD and Tenstorrent.

View original content to download multimedia:https://www.prnewswire.com/news-releases/moreh-showcases-high-performance-llm-inference-on-amd-gpus-at-amd-advancing-ai-2026-302833887.html

SOURCE Moreh

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