UWCISA’s 6 Tech Takeaways: Power, Partnerships, and Pressure in AI

When we look at the rivalry within the AI world, we see that competition is running along at least three axes at once: financial performance, geopolitical alignment, and architectural philosophy. 

Counterpoint Research data put Anthropic ahead of OpenAI in Q1 2026 LLM revenue (31.4% vs 29%) with roughly 134 million monthly users against OpenAI's 900 million. Anthropic's average revenue per active user sits near $16.20 against OpenAI's $2.20, which is what put the smaller player at the top of the revenue table. Microsoft's Copilot Cowork, built jointly with Anthropic, shows that even OpenAI's largest investor is hedging, while OpenAI itself is missing internal growth targets even as it commits hundreds of billions in data center spend. The geopolitical layer is just as active: Washington is pressing allies on Chinese model "distillation," Beijing has forced Meta to unwind its Manus deal, and DeepSeek V4 is shipping with explicit Huawei chip support. At the same time, Airbnb's customer service agent runs on Alibaba's Qwen because, in Brian Chesky's words, it is "fast and cheap," a choice that now sits in front of a House committee. 

The fault line that matters is no longer which American lab wins, but whether the open-source Chinese stack or the proprietary American stack becomes the default substrate for global enterprise AI. Once a default takes hold, switching costs and compliance regimes tend to lock it in for a decade.

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1. Washington Escalates AI Tensions with Global Warning on China

The U.S. State Department has launched a global diplomatic effort warning allies about alleged attempts by Chinese companies, including AI startup DeepSeek, to extract and replicate American artificial intelligence models. According to a diplomatic cable, U.S. officials are urging foreign governments to be cautious of “distillation” practices—where smaller AI systems are trained using outputs from more advanced models—arguing this could enable foreign firms to mimic U.S. technology at a fraction of the cost while potentially removing built-in safety measures. The accusations echo earlier warnings from OpenAI and the White House, though China has firmly denied the claims, calling them baseless and politically motivated. Meanwhile, DeepSeek continues to advance its technology, recently unveiling a new model compatible with Huawei chips, underscoring China’s growing independence in AI development.

Global Warning Issued: The U.S. is actively urging allies to be cautious about Chinese AI firms allegedly replicating American models.

Debate Over “Distillation”: The controversy centers on AI training techniques that may copy outputs from advanced systems at lower cost.

Rising Tech Tensions: The dispute risks escalating U.S.-China competition despite recent diplomatic easing.

(Source: Reuters)

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2. Power Play Intensifies: China Forces Meta to Unwind AI Deal

Meta is preparing to unwind its $2.5 billion acquisition of AI startup Manus after Chinese regulators blocked the deal on national security grounds, highlighting escalating control over cross-border AI technology. The startup, which has ties to China despite operating through Singapore, had already been partially integrated into Meta’s systems, making a reversal technically and financially complex. Beijing has reportedly ordered a full separation, including restoring Chinese assets and removing any transferred data or technology, with potential penalties if the process is incomplete. The move signals a broader strategy by China to retain AI capabilities within its borders and limit foreign access, even at the cost of discouraging international investment.

Deal Reversal: Meta may be forced to undo a major AI acquisition due to Chinese national security concerns.

Data Sovereignty: China is tightening control over AI technology and cross-border transfers.

Global Fragmentation: Tech companies face increasing risk from geopolitical barriers to deals and partnerships.

(Source: The Wall Street Journal)

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3. Why DeepSeek’s V4 Could Reshape the AI Landscape

DeepSeek’s newly released V4 model represents a significant step forward in open-source artificial intelligence, offering performance comparable to leading proprietary systems at a fraction of the cost. The model introduces major technical improvements, including a massive one-million-token context window and a more efficient attention mechanism that reduces computing and memory demands while handling large-scale data. Available in two versions—V4-Pro for complex tasks and V4-Flash for faster, cheaper deployment—it is positioned as one of the most powerful open-source models to date, particularly in coding and technical problem-solving. Beyond performance, V4 highlights China’s broader push for AI independence, as it is optimized for domestic chips like Huawei’s Ascend.

Open-Source Breakthrough: V4 delivers top-tier AI performance at significantly lower costs, making advanced AI more accessible.

Efficiency Innovation: Its new architecture dramatically improves memory use and enables processing of extremely large inputs.

Strategic Shift: The model supports Chinese-made chips, signaling a move toward technological independence from U.S. hardware.

(Source: MIT Technology Review)

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4. Cracks Emerge in OpenAI’s High-Stakes Race for AI Dominance

OpenAI is facing mounting internal concerns after missing key revenue and user growth targets, raising questions about its aggressive spending strategy as it eyes a potential IPO. Executives, including CFO Sarah Friar, have reportedly warned that slowing growth could make it difficult to sustain the company’s enormous commitments to data center infrastructure, which total hundreds of billions of dollars. While CEO Sam Altman continues to push for securing vast computing resources to fuel future AI demand, some board members are urging greater financial discipline. The company has also faced increased competition from rivals like Google and Anthropic, impacting revenue and market share.

Missed Targets: OpenAI fell short on both user growth and revenue expectations, raising internal concerns.

Spending Pressure: Massive data center investments are under scrutiny as growth slows.

IPO Uncertainty: Financial discipline and operational readiness are becoming critical ahead of a potential public listing.

(Source: The Wall Street Journal)

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5. Anthropic’s Mythos AI Sparks Fears of a New Cybersecurity Era

Anthropic’s latest AI model, Mythos, is raising significant concern across the tech industry due to its unprecedented cybersecurity capabilities and advanced reasoning skills. Unlike typical AI releases, the company has chosen not to make Mythos publicly available, citing risks that its powerful ability to detect and potentially exploit software vulnerabilities could be misused. Instead, access is being limited to cybersecurity experts and major organizations through a controlled initiative aimed at identifying and fixing system weaknesses. While these capabilities could greatly enhance defensive cybersecurity, experts warn they may also enable more sophisticated cyberattacks if the technology falls into the wrong hands.

Restricted Release: Anthropic is limiting access to Mythos due to concerns over misuse and security risks.

Powerful Capabilities: The model can detect deep vulnerabilities and demonstrates highly advanced reasoning.

Security Trade-Off: While useful for defense, Mythos could enable more dangerous cyberattacks if misused.

(Source: MSN)

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6. Microsoft and Anthropic Signal a New Era of AI-Powered Work

Microsoft’s Copilot Co-Work initiative reflects a broader shift in the AI industry toward deeply integrated, enterprise-ready systems—an approach that aligns closely with partners like Anthropic. While Copilot acts as an embedded “co-worker” across Microsoft 365, enabling real-time collaboration, automation, and decision support, its evolution also highlights the importance of combining powerful AI capabilities with safety and reliability. Microsoft’s partnership with Anthropic underscores a growing emphasis on responsible deployment as AI systems become more autonomous in the workplace.

Strategic Alignment: Microsoft’s AI direction complements Anthropic’s focus on safe, controlled deployment.

AI as Infrastructure: Copilot Co-Work embeds AI deeply into everyday workflows and collaboration.

Partnership-Driven Future: Major AI advancements are increasingly shaped by alliances between leading firms.

(Source: Microsoft)

UWCISA's 5 Tech Takeaways: Big Bets, Quiet Progress, and What Comes Next

A key question is on everyone's mind: how are companies using GenAI? 

WSJ attempts to answer this question (see link below). Here's what I found relevant from the article:

Automating existing workflows:  Companies are using AI to speed up processes that were already being streamlined with older automation tools. The big difference now is that AI can handle "unstructured data"—meaning it can read and extract information from things like emails, Word documents, and PDFs that older software couldn't easily process. This lets companies connect messy, human-written content to their existing automated systems.

Summarizing content: One of the most common uses is having AI condense large amounts of text—reports, documents, meeting notes, research—into shorter summaries. All this is widespread it's "not that exciting."

Research tasks: AI is handling what the reporters call "really boring research"—the kind of tedious information-gathering that used to eat up employee time. I've found DeepResearch to be an excellent tool to do a first pass at an exploratory research task. At a minimum, you get a list of links that can be a good starting. 

Customer service: AI is answering customer calls and powering chatbots. The reporters note that while the technology has existed for years, companies were initially afraid to let AI talk directly to customers (worried about hallucinations, mistakes, or even hacking incidents where chatbots were manipulated into saying inappropriate things). For what can go wrong, check out Air Canada's experience. 

Writing code: Developers are using tools like GitHub Copilot and Claude Code to help write software. One reporter mentioned that companies are rethinking hiring because of this—instead of hiring 100 engineers, they might only need five if AI handles some of the coding work.

AI at Work: Big Promises, Small but Steady Gains

Despite bold claims from executives, corporate AI adoption is often quieter and more incremental than transformative. Companies are primarily using AI to automate existing workflows, summarize content, and support customer service rather than reinventing entire operations. While interest in autonomous “agentic” AI is growing, most organizations remain cautious, keeping humans in the loop due to concerns over reliability and trust. Leaders remain optimistic about AI’s long-term value, focusing on efficiency gains and future competitiveness rather than immediate financial returns.

Key Takeaways

• Most AI gains are incremental: Companies are seeing steady improvements in productivity without dramatic operational overhauls.
• Trust limits autonomy: Concerns about errors and hallucinations are preventing widespread deployment of fully autonomous AI agents.
• Leadership drives success: Organizations where top executives actively champion AI tend to see deeper and more effective adoption.

(Source: Wall Street Journal)

Inside Satya Nadella’s Plan to Reinvent Microsoft for the AI Era

Microsoft CEO Satya Nadella has launched a sweeping overhaul of the company’s senior leadership as he pushes to strengthen Microsoft’s artificial intelligence strategy beyond its once-exclusive partnership with OpenAI. Facing intensifying competition from rivals such as Alphabet and Amazon, Nadella has made high-profile external hires, reshuffled internal responsibilities, and adopted a more hands-on, “founder mode” leadership style to accelerate innovation. These changes aim to speed the development of Microsoft’s own AI models, coding tools, and applications while cutting internal bureaucracy. The move follows a restructuring of Microsoft’s relationship with OpenAI that will gradually reduce Microsoft’s privileged access to its partner’s models, forcing the company to build a more independent AI future.

Key Takeaways

• Leadership shake-up to boost speed: Nadella has restructured Microsoft’s senior leadership to reduce bureaucracy and accelerate decision-making around AI development.
• Preparing for life beyond OpenAI: With exclusive access to OpenAI’s models set to fade over time, Microsoft is investing heavily in building its own AI models and internal capabilities.
• Competition driving urgency: Increased pressure from rivals and AI start-ups is forcing Microsoft to move faster and rethink how it executes its AI strategy.

(Source: Financial Times)

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No Slowdown Ahead: Why AI’s Momentum Will Carry Into 2026

The rapid expansion of artificial intelligence shows no signs of slowing as 2026 approaches, according to a Dalhousie University computer science professor. AI has become deeply integrated into everyday life, powering tools such as weather forecasting, medical diagnostics, and decision-support systems while dramatically reducing computational costs. However, the growing sophistication of AI also brings risks, including more advanced phishing attacks and potential psychological effects on users. Experts say stronger regulation and widespread education will be essential as AI becomes more personalized and embedded across society.

Key Takeaways

• AI adoption will continue accelerating: Experts expect AI tools to become more powerful, specialized, and widely used throughout 2026.
• Benefits are tangible and growing: AI is already delivering measurable improvements in efficiency, accuracy, and cost reduction across multiple industries.
• Risks must be addressed: Increased use of AI raises concerns around cybersecurity, mental health, and misinformation that require regulation and education.

(Source: BNN Bloomberg)

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Meta’s AI Buying Spree Continues With Manus Acquisition

Meta Platforms has acquired Manus, a Singapore-based developer of general-purpose AI agents, as part of its aggressive push to expand automation across consumer and enterprise products. Manus experienced rapid growth after launching its AI agent earlier this year, claiming more than $100 million in annualized revenue within eight months. Meta plans to integrate Manus’s technology into products such as its Meta AI assistant while allowing the company to continue operating independently. The deal highlights Meta’s broader strategy of acquiring AI start-ups to secure talent and technology amid intensifying competition.

Key Takeaways

• Meta is betting big on AI agents: The acquisition strengthens Meta’s push to automate complex tasks across its consumer and business products.
• Manus scaled at extraordinary speed: The start-up’s rapid revenue growth underscores strong demand for AI agent technology.
• Talent acquisition remains critical: Meta continues to use acquisitions to secure AI expertise and stay competitive in the AI arms race.

(Source: CNBC)

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Inside Nvidia’s $20 Billion Groq Deal — And Who Gets Paid

A complex $20 billion agreement between Nvidia and AI chip start-up Groq is delivering substantial payouts to employees and investors without a traditional acquisition or equity transfer. Under the non-exclusive licensing deal, most Groq employees are expected to join Nvidia with a mix of cash payouts and stock, while Groq continues operating independently. The structure reflects a growing trend in AI dealmaking designed to secure talent and technology while minimizing antitrust risk, highlighting the enormous financial stakes surrounding AI hardware innovation.

Key Takeaways

• A non-traditional deal structure: Nvidia avoided a full acquisition while still valuing Groq at $20 billion through a licensing agreement.
• Employees and investors benefit significantly: Most Groq shareholders and staff are receiving major cash and stock payouts, often with accelerated vesting.
• Antitrust pressure is shaping AI deals: Big Tech companies are increasingly using creative deal structures to avoid regulatory scrutiny.

(Source: Axios)

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Author: Malik D. CPA, CA, CISA. The opinions expressed here do not necessarily represent UWCISA, UW,  or anyone else. This post was written with the assistance of an AI language model. 

The AI Bubble in Focus: Why It Feels Familiar

This week, we’re diving into something that’s hard to ignore right now: the AI bubble. 

The idea came from a Bloomberg graphic showing the circular flow of money within the AI ecosystem. Although I saw it before, I saw it again on YouTube. So I thought it would be a good idea to focus this week's post on the topic. 

From: Here

Bubbles are nothing new. They’re part of capitalism’s DNA. A good framework to think about this is the Gartner Hype Cycle. It maps out two main forces that shape how technology evolves. The first is the S-curve — that natural, steady climb of genuine technological progress. The second is the hype curve — that euphoric rush of money and optimism that tends to overshoot what the tech can actually do.

That gap between expectation and reality is where the trouble usually starts. It’s also where Gartner’s so-called trough of disillusionment begins — and, as Gartner points out, generative AI has officially entered that stage. If you’re not familiar with the hype cycle, it’s worth checking out. It helps make sense of why so many people are starting to feel that uneasy mix of excitement and skepticism right now.

This topic also connects back to some early research I did with Professor Efrim Boritz at the University of Waterloo on the concept of bubbles: work that actually came out just before Gartner released their model. We looked at how bubbles have shown up again and again: the railway bubble, the radio bubble that set the stage for the 1929 crash, the dot-com bubble, and so on. These aren’t random events; they’re patterns.

So yes, it’s probably fair to say we’re in a bubble now. That’s not investment advice (I am in risk management after all!): just an observation based on history. The Bloomberg piece and its “circular flow” chart tell one side of the story, but the other side is economic: the Magnificent Seven tech giants are booming while the rest of the economy struggles. That imbalance matters, and it could have some dramatic ripple effects.

And, if history is any guide, when the music stops, auditors and accountants are usually among the first to face the spotlight — whether they deserve it or not. New accounting rules and oversight frameworks always seem to appear after something breaks. Think about it:

• The Savings and Loan crisis in the ’80s gave us the COSO framework and the Treadway Commission.
• The Enron and WorldCom scandals led to Sarbanes–Oxley.
• The 2008 financial crisis brought Dodd–Frank.

So the real question isn’t just whether there’s an AI bubble — it’s what will come after it bursts. Every bubble leaves behind more than just wreckage; it reshapes how we account for risk, trust, and innovation.

AI at the Crossroads: Boom, Bubble, or Rebuild?

1. Inside the $1 Trillion AI Boom: OpenAI’s Circular Deals with Nvidia and AMD

OpenAI has struck massive, multi‑billion dollar deals with both Nvidia and AMD in an effort to secure the computing power it needs to stay ahead in the AI race. These agreements—up to $100 billion with Nvidia and a significant multi‑gigawatt arrangement with AMD—are fueling what experts predict could be a $1 trillion AI infrastructure surge. But the structure of these deals, with equity swaps and reciprocal commitments, has raised concerns that the growth may be more circular than sustainable. Analysts warn that while this could reshape the AI hardware ecosystem, it also introduces new risks around transparency, regulation, and long‑term value. (Source: Bloomberg)

• OpenAI’s infrastructure expansion: The company is scaling its compute capabilities dramatically, including a 10 gigawatt GPU commitment from Nvidia.
• Circular investment structures: Deals involving equity stakes and purchase commitments between OpenAI, Nvidia, and AMD raise questions about the sustainability and true demand of AI infrastructure growth.
• Market risks and scrutiny: Despite the potential for a $1 trillion AI boom, experts highlight concerns about profitability, supply chain limitations, and looming regulatory oversight.

See here for Bloomberg Intelligence's coverage of this.

2. Investors Revisit 1999: How the AI Boom is Echoing the Dot‑Com Era

As AI investment fever grips global markets, many investors are turning to old strategies to navigate what could be another tech bubble. Reuters reports that hedge funds and asset managers are pulling back from the most overhyped AI stocks and shifting toward undervalued adjacent sectors like robotics, clean energy, and Asian tech. The article draws sharp comparisons to the dot‑com boom, pointing out the concentration of market performance in a few companies and the increasingly speculative nature of some AI plays. (Source: Reuters)

• Investor strategy adjustment: Instead of piling into top AI‑stocks, many are repositioning into overlooked sectors (e.g., robotics, Asian tech, uranium) to ride the wave while avoiding peak‑risk.
• Echoes of dot‑com excess: The environment mirrors 1999‑2000’s tech boom—with extreme valuations, concentration in a few companies, and risks of overcapacity and hype.
• Dual scenario risk: If AI delivers as promised, investors will be rewarded; but if the productivity gains don’t materialize or costs escalate, a sharp correction could follow.

3. Hype Cycle Refresh: What does Gartner say about AI & Hype? 

According to Gartner’s 2025 Hype Cycle for Artificial Intelligence, GenAI has officially entered the “Trough of Disillusionment” as organizations begin to grasp its limitations. While many struggle to prove ROI on AI investments, the attention is shifting toward foundational technologies like AI-ready data, AI agents, and ModelOps. These building blocks are seen as critical for operationalizing AI at scale and ensuring long-term success. The report also notes a growing emphasis on governance, security, and real-world deployment, marking a maturation of enterprise AI strategy. (Source: Gartner)

• GenAI’s changing role: Generative AI has reached the “Trough of Disillusionment” as expectations meet reality and many organizations fail to see clear returns.
• Foundational technologies rising: AI‑ready data and AI agents are among the fastest‑moving innovations in 2025, showing where investment is shifting for scalable AI.
• Governance and operations matter: For AI to deliver value, enterprises must focus on infrastructure (ModelOps), governance (risk, bias, security), and data management — not just on building large models.

4. When AI Powers the Market: How the Infrastructure Boom Is Shaping Stocks

The U.S. stock market’s recent highs are largely fueled by AI-related stocks. Investopedia details how massive capex from tech giants like Microsoft, Alphabet, and Meta is driving growth in chipmakers and software companies, many of which are seeing their stock prices soar. But the article also warns that “circular” investments—where companies fund each other while purchasing each other’s products—could be fragile. If investor sentiment shifts or AI returns disappoint, the entire market could face a downturn. (Source: Investopedia)

• AI stocks as market engines: Many of the top‑performing stocks in the S&P 500 are tied to AI and have helped sustain the broader bull market.
• Massive infrastructure build‑out: Tech giants are significantly increasing capex to support AI infrastructure, which is fueling growth in chipmakers and related firms.
• Bubble risks loom: The article warns that circular deals and high valuations could leave the market vulnerable if AI investment returns don’t meet expectations.

5. The AI Bubble: What will be the Bloody Aftermath?

Eduardo Porter’s piece in The Guardian takes a sobering look at the economic fragility masked by AI’s explosive growth. While tech investment is propping up stock prices and business activity, the real economy—wages, employment, consumer stability—is showing signs of stress. Porter argues that a collapse of the AI bubble might be painful but necessary, providing an opportunity to reorient AI development toward augmenting rather than replacing human labor and to address the concentration of wealth and power in tech giants. (Source: The Guardian)

• Economic fragility behind the boom: Despite dazzling investment in AI, fundamentals like employment growth and wages are weak — signalling underlying fragility.
• The bubble risk with wide consequences: If the AI‑investment bubble bursts, the fallout wouldn’t just hit tech companies — the broader economy could follow.
• A potential reset with social opportunity: The article suggests that a correction could open the door to re‑orienting AI toward human‑centric outcomes and more equitable economic structures.

Author: Malik D. CPA, CA, CISA. The opinions expressed here do not necessarily represent UWCISA, UW,  or anyone else. This post was written with the assistance of an AI language model. 

AI News This Week: Infrastructure, Innovation, and Education

UWCISA Blog · AI on the Edge: Infrastructure, Innovation, and Education

📰 AI Overbuild: China’s Risky Bet on Data Center Expansion

China has poured billions into building data centers to fuel its AI ambitions, but a new report reveals that up to 80% of this capacity is currently unused. Driven by government initiatives and private investment, more than 500 centers were launched, though many are now idle due to shifting AI demands and poor infrastructure planning. Technologies like DeepSeek have pivoted AI interest from model training to inference, making much of the infrastructure obsolete. Developers are resorting to giveaways and GPU selloffs, raising fears that a wave of excess capacity could disrupt the global data center market.

Source: TechRadar

• Idle Infrastructure: Up to 80% of China’s new data center capacity is currently unused.
• Shift in AI Focus: Tools like DeepSeek’s R1 model have moved the emphasis from training to inference, rendering many training-oriented data centers obsolete.
• Market Impact Risk: If unused capacity hits the general market, it could significantly disrupt prices and investor confidence.

🧠 Agentic vs. Generative AI: What’s the Real Difference?

As artificial intelligence continues to evolve, two distinct forms — Generative AI (Gen AI) and Agentic AI — are shaping the future of automation and decision-making. Gen AI is designed to create original content like text, images, and code based on user input, using deep learning models that emulate human language and logic. In contrast, Agentic AI represents the next leap forward: AI systems capable of acting autonomously, making decisions, and pursuing complex goals with minimal human intervention. These systems blend large language models with machine learning, reinforcement learning, and context awareness to perceive, reason, act, and learn independently.

The article emphasizes that Gen AI is reactive, producing content when prompted, while Agentic AI is proactive, capable of adjusting to its environment and taking initiative. Use cases for Gen AI include SEO content creation, customer support chatbots, and product design, whereas Agentic AI is being tested in sectors like logistics, finance, healthcare, and even city planning. Despite its promise, Agentic AI remains largely experimental, and the distinction between it and traditional AI agents is important: Agentic AI is the overarching framework, while AI agents are the functional components executing tasks within it.

Source: IBM

• Core Difference: Generative AI creates content; Agentic AI autonomously makes decisions and performs tasks with limited oversight.
• Autonomous Capabilities: Agentic AI uses perception, reasoning, and action loops to operate proactively in dynamic environments.
• Emerging Applications: While Gen AI is widely adopted, Agentic AI is being explored in complex domains like urban planning, finance, and robotics.

💡 Microsoft’s Copilot Gets Smarter: Memory, Vision, and a Touch of Clippy

To celebrate its 50th anniversary, Microsoft has rolled out a sweeping update to its Copilot AI assistant, significantly enhancing its capabilities and personalization features. Built on OpenAI models, the updated Copilot now includes Memory, allowing it to retain user preferences, interests, and even personal details like birthdays to offer more tailored suggestions. Users can control what Copilot remembers or choose to opt out.

New additions like Actions enable the AI to interact with websites directly—booking tickets, making purchases, or navigating the web—similar to tools like OpenAI's Operator. Copilot Vision, previously limited to web tools, now expands to Windows and mobile platforms, offering real-time screen and camera analysis to answer questions or help manage documents. Another standout feature is Deep Research, which lets Copilot analyze massive datasets or documents to support complex projects and integrates tightly with Bing search.

Microsoft also introduced podcast generation capabilities and a new Pages feature to help organize information across files. While many of these tools mirror capabilities already available in competing AI platforms, Microsoft’s decision to launch them all at once demonstrates a robust effort to stay competitive and to deliver a deeply personalized AI experience. Oh, and yes—Clippy might be making a comeback.

Source: The Verge

• Major Feature Expansion: Microsoft Copilot now supports memory, personalization, web actions, podcast creation, and document analysis.
• User-Centric Customization: Copilot can remember user preferences and soon offer a personalized visual interface—possibly including Clippy.
• Competitive Push: With many features mirroring rivals like ChatGPT and Google Gemini, Microsoft is aggressively enhancing Copilot to maintain AI leadership.

🦙 Meta Unleashes LLaMA 4—But the Real AI Powerhouse Is Yet to Come

Meta has officially unveiled its latest suite of large language models, LLaMA 4, as part of its ongoing effort to stay competitive in the generative AI space. While the new models are available now to developers and researchers, CEO Mark Zuckerberg emphasized that Meta’s most powerful AI model is still in development, hinting at an even more advanced system expected to launch later in 2025. LLaMA 4 builds on the success of its predecessor by enhancing performance, safety, and scalability, with multiple versions designed to meet varied application needs.

A key distinction in Meta’s approach is its open-source strategy, which aims to foster community collaboration and innovation—contrasting sharply with competitors like OpenAI and Anthropic, who have kept their most powerful models proprietary. Meta plans to integrate LLaMA 4 into its suite of products, including WhatsApp, Instagram, and Facebook, and even roll out AI agents that users can interact with directly in-app. Additionally, Meta is laying the groundwork for a public AI infrastructure, allowing businesses to build their own applications atop Meta’s models through APIs and developer tools.

Zuckerberg positioned this latest release not as an endpoint, but as a stepping stone toward a future where AI is deeply embedded across consumer and enterprise tools. With one eye on rival advancements and the other on a larger vision for democratized AI access, Meta is staking a major claim in the AI landscape.

Source: CNBC

• LLaMA 4 Released: Meta launched new versions of its open-source AI models, with broader integration planned across its apps.
• More to Come: CEO Mark Zuckerberg revealed Meta’s most powerful model is still in development and slated for a 2025 release.
• Open Source Focus: Meta continues to differentiate itself with a transparent, community-first approach to AI development.

🏆 Microsoft Launches Global AI Skills Fest with Record-Breaking Ambitions

In a creative and ambitious push to both democratize AI education and set a Guinness World Record, Microsoft has launched its AI Skills Fest—a 50-day global training initiative offering free AI education to learners of all levels. The event aims to have over 46,046 participants complete a multi-level AI lesson within 24 hours between April 7 and 8, 2025, breaking the current record for most users completing an online AI course in a day. The fest includes a mix of beginner-friendly tutorials and more advanced modules on topics like machine learning, natural language processing, and Microsoft’s Azure and Copilot tools.

The training is available in over 30 languages and includes everything from self-paced lessons and hackathons to sweepstakes and discount codes. Microsoft has gamified the experience with prizes like certification vouchers and even a LinkedIn-eligible participation badge. While it may have a playful marketing tone, the initiative also serves a broader mission: to equip more people with AI literacy at a time when demand for these skills is soaring. GitHub, a Microsoft subsidiary, is also participating by offering discounts on its Copilot certification for developers.

With both accessibility and fun at the forefront, AI Skills Fest not only promotes education but turns learning into a global event—blending practical upskilling with a touch of spectacle.

Source: ZDNet

• AI for All: Microsoft’s AI Skills Fest offers free training for all experience levels in a wide variety of AI topics and tools.
• Guinness World Record Attempt: The company hopes to break the record for the most users completing an AI course in 24 hours.
• Gamified Learning: Participants can earn badges, win certification vouchers, and join community events while gaining practical AI skills.

Five Top Tech Takeaways: Apple Unveils AI at WWDC, OpenAI Pays VOX/Atlantic a Cut, Claude Comes to Canada and more!

Apple's AI

Apple Introduces 'Apple Intelligence' with Advanced AI Features

At WWDC 2024, Apple introduced "Apple Intelligence," a suite of AI features for iPhone, Mac, and other devices, to be released in the fall. Highlights include a more conversational Siri, AI-generated "Genmoji," and integration with OpenAI's GPT-4o for advanced queries. These features, designed to enhance user interaction and productivity, will operate primarily on-device for privacy, utilizing Apple's Private Cloud when necessary. Siri will now support more natural speech and typed commands, perform actions across apps, and assist with tasks like email composition and photo editing.

To see a 2-minute summary, check out CNETs time-saving montage (start at 9:27 for the AI-related announcements):

Key Takeaways:

1. Apple unveiled "Apple Intelligence," featuring enhanced AI capabilities for iPhone, Mac, and more.
2. Siri will become more conversational and capable of handling advanced tasks using OpenAI’s GPT-4o.
3. Privacy remains a priority, with AI processing on-device and through Apple's Private Cloud.

(Source: The Verge)

Claude AI Assistant Launches in Canada

Claude, Anthropic's advanced AI assistant, is now available in Canada through various platforms including Claude.ai, a free iOS app, and an API for developers. The service also offers a Team plan for collaborative use. Users can subscribe to Claude Pro for CA$28 per month to access all models and receive increased usage benefits. The Team plan, at CA$42 per user per month, requires a minimum of five users. This expansion aligns with Canada's commitment to responsible AI development and provides new opportunities for users to integrate advanced AI into their workflows.

Key Takeaways:

• Claude, an AI assistant by Anthropic, is now accessible in Canada via web, iOS app, and API.
• Claude Pro subscription offers enhanced features and usage for CA$28 per month.
• The Team plan provides a collaborative workspace for CA$42 per user per month, requiring a minimum of five users.

(Source: Anthropic)

US Regulators Probe Nvidia, Microsoft, and OpenAI for Antitrust Violations

The U.S. Department of Justice (DOJ) and Federal Trade Commission (FTC) are launching investigations into Nvidia, OpenAI, and Microsoft. The DOJ will focus on potential antitrust violations by Nvidia, while the FTC will probe Microsoft and OpenAI's actions. Specifically, the FTC is examining whether Microsoft structured its deal with Inflection AI to evade regulatory scrutiny. Microsoft's spokesperson asserts the company’s compliance with legal obligations. These probes highlight regulatory efforts to scrutinize AI ventures more rigorously and prevent potential antitrust violations.

Key Takeaways:

• The DOJ and FTC are investigating Nvidia, OpenAI, and Microsoft for potential antitrust violations.
• The FTC is specifically probing whether Microsoft’s deal with Inflection AI was structured to avoid regulatory oversight.
• Microsoft maintains that its agreements and transactions comply with legal requirements.

(Source: Yahoo Finance)

OpenAI Continues Media Expansion with New Licensing Agreements

OpenAI has secured licensing agreements with The Atlantic and Vox Media, allowing their content to train AI models and be shared within ChatGPT. This move follows similar deals with News Corp, Axel Springer, DotDash Meredith, the Financial Times, and The Associated Press, aimed at acquiring legal content for AI training and avoiding copyright issues. Terms for The Atlantic and Vox Media were not disclosed, but such agreements typically involve content attribution and financial compensation. Vox Media will use OpenAI's technology to enhance its commerce and advertising platforms, while The Atlantic plans to develop AI tools for journalism.

Key Takeaways:

• OpenAI signed content licensing agreements with The Atlantic and Vox Media for AI model training and sharing within ChatGPT.
• These deals aim to secure legal training data and prevent copyright lawsuits, following similar agreements with other major media companies.
• Vox Media and The Atlantic will use OpenAI's technology to enhance their digital products and develop AI tools for better journalism.

(Source: The Verge)

AI Meets Curation: Perplexity Pages Blend Automation and Human Input

Perplexity AI has launched "Perplexity Pages," a feature that transforms search queries into visually appealing, shareable web pages. Users can create detailed articles by entering prompts and selecting an audience type to tailor the content. The tool allows for customization, including rewriting, reformatting, and adding sections. These pages, which can include relevant media, are searchable on Google and sharable via links. Perplexity Pages aims to blend AI-driven content generation with human curation, offering a new way to produce and share information-rich web pages.

Key Takeaways:

• Perplexity AI's new feature converts search queries into detailed, shareable web pages.
• Users can customize the generated content and include media, making it searchable and shareable. 
• The feature blends AI content generation with human curation, emphasizing user input in organizing and presenting information.

(Source: TechCrunch)

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist who is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else. This post was written with the assistance of an AI language model. The model provided suggestions and completions to help me write, but the final content and opinions are my own.

Five Top Tech Takeaways: Microsoft Unveil AI PCs, Google's $125B Cloud Glitch, Battle of the Bots, Glue Pizza, and GPT4 Outshines in Financial Forecasting

Make an image of a battle royale with the 5 robots with logos instead of heads. This includes the Google logo, Microsoft logo, OpenAI logo, Perplexity AI logo, and Anthropic logo

Battle of the Bots: WSJ's Comprehensive GenAI Evaluation 

A comprehensive test by the Wall Street Journal compared five top AI chatbots—OpenAI's ChatGPT, Microsoft's Copilot, Google's Gemini, Perplexity, and Anthropic's Claude—on everyday skills. The tests included tasks in health, finance, cooking, work writing, creative writing, summarization, current events, coding, and speed. Perplexity emerged as the overall winner, excelling in summarization and current events, while ChatGPT performed best in health advice and speed. Each chatbot demonstrated unique strengths and weaknesses, highlighting the rapid evolution and diverse capabilities of AI technology.

Key Takeaways:

• Perplexity outperformed other AI chatbots in summarization and current events tasks.
• Claude excelled at work and creative writing.
• ChatGPT had the fastest response time.

(Source: Wall Street Journal)

Author's note: 

The Wall Street Journal's exercise is a valuable reminder that organizations must conduct a thorough and rigorous analysis of Generative AI (GenAI) vendors, just as they would with any other software procurement. The article provides a solid foundation for testing and evaluating these tools. However, it is crucial to note that effective testing can only be carried out once the potential business benefits have been clearly identified.

To ensure a comprehensive evaluation, organizations should first determine which specific functions will utilize the AI-powered chatbots and establish clear guidelines on how they will be used and managed within the company. This groundwork will enable the development of targeted test prompts, allowing for a more accurate assessment of which chatbot is best suited to meet the organization's unique needs and requirements. By aligning the testing process with the identified business objectives, companies can make informed decisions when selecting the most appropriate GenAI vendor for their specific use cases.

Microsoft Unveils AI-Powered Copilot+ PCs

Microsoft introduced the Copilot+ PCs, a new category of AI-enhanced Windows PCs with advanced silicon offering up to 40+ TOPS, extended battery life, and innovative AI features. These PCs feature Recall for memory-like data retrieval, Cocreator for real-time AI image creation, and live audio translation from 40+ languages. Starting at $999, they will be available from June 18 and include models from Microsoft Surface and other major brands.

Key Takeaways

• Microsoft launched Copilot+ PCs, integrating advanced AI capabilities and powerful silicon.
• Features include Recall for data retrieval, Cocreator for AI-driven image creation, and live translation.
• The devices, starting at $999, will be available from June 18 from multiple major brands.

(Source: Microsoft)

From Glue on Pizza to Eating Rocks: Google's AI Under Fire

Google's new AI-generated search overviews have been widely mocked for providing bizarre and incorrect responses to user queries. Examples include recommending eating rocks based on a humor website, suggesting glue for pizza cheese, and sharing incorrect and offensive information about former President Obama. These errors highlight significant limitations and "hallucinations" in AI technology, prompting criticism and calls for better safeguards and accuracy in AI-generated content.

Key Takeaways

• Google's AI search overviews have produced absurd and incorrect answers, causing social media backlash.
• Errors included recommending glue for pizza and sharing false information about former President Obama.
• Google's AI issues underline broader challenges in AI technology, especially regarding accuracy and reliability.

GPT-4 Outshines Humans in Financial Forecasting

A study by the Booth School of Business at the University of Chicago found that OpenAI's GPT-4 outperforms human financial analysts in predicting earnings changes from financial statements. Using "chain-of-thought" prompts, GPT-4 achieved a 60% accuracy rate compared to the low 50% range of human analysts. Additionally, trading strategies based on GPT-4's forecasts yielded more profitable results than traditional stock market approaches, suggesting significant potential for AI in financial decision-making.

Key Takeaways

• GPT-4 surpasses human analysts in financial earnings predictions.
• The AI model achieved a 60% accuracy rate, higher than human analysts.
• GPT-4-based trading strategies generated higher profits than the stock market.

(Source: Business Insider)

Google's Cloud Glitch: UniSuper's $125 Billion Account Erased

Google inadvertently deleted the Google Cloud account of UniSuper, an Australian pension fund managing $125 billion. This incident left over half a million fund members without account access for about a week. UniSuper restored service via a backup account with another cloud provider. Google Cloud CEO Thomas Kurian and UniSuper CEO Peter Chun acknowledged the severity of the situation and assured measures have been taken to prevent future occurrences.

Key Takeaways:

• Google accidentally erased a $125 billion pension fund's Google Cloud account, affecting over half a million users.
• The issue was resolved using a backup account with another cloud provider.
• Google and UniSuper CEOs stated measures are in place to prevent similar incidents.

(Source: Yahoo)

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist who is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else. This post was written with the assistance of an AI language model. The model provided suggestions and completions to help me write, but the final content and opinions are my own.

Five Top Tech Takeaways: AI Rapping Mona Lisa, Calls for AI Oversight, AI in the Banks, AI Art Receives Limited Copyright and Meta Competes with ChatGPT

Lights, Camera, Robots!

Movie Maker's Dream or Deep Fake Nightmare? Microsoft's AI Animates Art with Caution

Microsoft's latest AI innovation, detailed by their researchers last week, introduces an AI model capable of animating still images into realistic videos synchronized with audio. The VASA-1 technology can produce lifelike animations from photos, artwork, or cartoons, featuring accurate lip-syncing and naturalistic movements of the face and head. Demonstrated with a video of the Mona Lisa rapping a comedy piece by Anne Hathaway, the technology aims to enhance educational tools, assist individuals with communication challenges, and possibly create virtual companions. 

However, concerns about potential misuse for impersonation and misinformation persist. Microsoft has decided to withhold the public release of VASA-1 to ensure responsible use, aligning with practices of cautious distribution similar to their partner OpenAI's approach with the AI video tool, Sora.

Author's note: As discussed in these two posts (here and here), the possibility of creating a Hollywood studio in one's garage is becoming more realistic. Many will highlight the challenges posed by deepfakes, which are undoubtedly significant. However, there is also a positive aspect to consider. These tools could potentially enable artists to tell their stories through a cost-effective model. In fact, Tyler Perry halted his $800 million studio construction plan, influenced by the advanced visual effects achievable through OpenAI's Sora, demonstrating the shifting economic landscape of Hollywood production.

Key Takeaways:

• Microsoft's new AI, VASA-1, animates still images into realistic videos with natural movements and synchronized audio.
• The technology showcases potential uses in education and accessibility, yet also raises significant concerns about misuse for creating false representations.
• Microsoft is withholding VASA-1's public release, focusing on responsible and regulated technology deployment.

(Source: CTV News)

For the original Microsoft post and more videos, see here. 

Former OpenAI Board Member Calls for Regulatory Oversight in AI

Former OpenAI board member Helen Toner advocated for increased transparency and regulation in the AI industry during a TED talk in Vancouver. Toner emphasized the necessity for AI companies to publicly disclose details about their technologies' capabilities and risks, and to implement robust data collection systems to address incidents. She proposed the establishment of "AI auditors" to ensure that companies are held accountable, rather than self-regulating, reflecting on her experiences and challenges, including her controversial tenure on OpenAI's board.

Key Takeaways:

• Helen Toner, ex-OpenAI board member, stressed the importance of AI companies being transparent about their technologies and the associated risks.
• Toner proposed the creation of independent "AI auditors" to oversee company practices and enhance accountability in the industry.
• Reflecting on her own experiences, Toner highlighted the need for effective incident reporting mechanisms within AI companies, akin to those in aviation.

(Source: Bloomberg)

Jamie Dimon Outlines AI’s Role in JPMorgan’s Future in Shareholder Letter

In JPMorgan Chase's latest shareholder letter, the critical role of artificial intelligence (AI) in the firm's growth and operations was highlighted. Over the past decade, the firm has significantly expanded its AI capabilities, now boasting over 2,000 AI and machine learning (ML) specialists and a robust portfolio of over 400 AI-driven use cases across various business sectors like marketing, fraud, and risk management. The firm is also exploring generative AI's potential to enhance software engineering, customer service, and general productivity. Recognizing AI's importance, a new executive role—Chief Data & Analytics Officer—has been established to ensure AI and data are integral to decision-making processes company-wide.

Key Takeaways:

• JPMorgan Chase has developed extensive AI and ML capabilities, with over 2,000 experts and 400 active AI use cases driving business improvements.
• The firm is actively exploring generative AI applications to reimagine business workflows and enhance overall productivity.
• A new executive role, Chief Data & Analytics Officer, has been created to integrate AI deeply into the company’s strategic and operational decisions.

(Source: JPMorgan Chase)

GenAI, Art, & Copyrights: USCO Grants Limited Copyright for AI-Assisted Work

Elisa Shupe successfully obtained copyright registration for her AI-assisted novel, "AI Machinations: Tangled Webs and Typed Words," from the US Copyright Office (USCO). Shupe extensively used OpenAI's ChatGPT while writing the book and initially faced rejection from the USCO. However, with the help of the Brooklyn Law Incubator and Policy Clinic, Shupe appealed the decision, arguing that she used ChatGPT as an assistive technology due to her disabilities. The USCO granted Shupe copyright for the selection, coordination, and arrangement of the AI-generated text, but not for the actual sentences and paragraphs. This decision is seen as a significant marker in how the USCO is grappling with the concept of authorship in the age of AI.

Key Takeaways:

• The US Copyright Office granted Elisa Shupe copyright registration for her AI-assisted novel, recognizing her as the author of the selection, coordination, and arrangement of the AI-generated text.
• Shupe's case highlights the nuances and challenges the USCO faces in determining the scope of protection for works produced using AI.
• The decision to grant Shupe a limited copyright registration is seen as a compromise, as she believes she should be able to copyright the actual text of the book due to her extensive involvement in the creative process.

(Source: Wired)

Explore Meta's Latest AI Innovation: Llama 3

Meta has introduced Meta Llama 3, their newest large language model (LLM), marking a significant advancement in AI capabilities. Llama 3, which includes models with 8B and 70B parameters, boasts state-of-the-art performance in various AI benchmarks and supports a wide range of applications with improved reasoning and coding abilities. These models will soon be available across major cloud platforms and feature enhancements in trust and safety with tools like Llama Guard 2 and CyberSec Eval 2. Meta's commitment to open-source development continues with the release of Llama 3, aimed at fostering innovation and responsible use in the AI community. 

Note: Meta.ai is available in Canada and you can try it out, here: https://www.meta.ai/

Key Takeaways:

• Meta Llama 3 introduces enhanced large language models with 8B and 70B parameters, setting new standards for AI performance and capabilities.
• The models are part of Meta's open-source initiative, ensuring broad accessibility and encouraging community-based innovation and development.
• Meta emphasizes responsible AI development, incorporating advanced safety features and guidelines to support secure and ethical usage.

(Source: Meta)

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist who is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else. This post was written with the assistance of an AI language model. The model provided suggestions and completions to help me write, but the final content and opinions are my own.

Five Top Tech Takeaways: SBF Gets 25, Getting "Glassdoored", Microsoft AI Expansion, $9 for AI Nurses, and Florida's Teen Social Media Ban

FTX Fallout: Sam Bankman-Fried handed a 25-Year Sentence

Sam Bankman-Fried, co-founder and former CEO of FTX, has been sentenced to 25 years in prison by the Southern District of New York Judge Lewis Kaplan for fraud and money laundering charges related to the crypto exchange's operations. This sentence comes after Bankman-Fried was found guilty on all seven counts, with a possible maximum of 110 years, during his trial. In addition to prison time, he is ordered to pay an $11 billion forfeiture to the U.S. government. The sentencing reflects the severity of the crimes, including the misuse of over $8 billion in customer funds. Bankman-Fried's case has been highlighted as a significant indicator for future legal actions within the crypto industry, emphasizing the need for deterrence against similar fraudulent activities. The outcome also underscores the absence of parole in the federal system, though good behavior could lead to a sentence reduction under the First Step Act.

(Source: TechCrunch)

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For more on SBF's sentencing, check Coffeezilla's take:

From Anonymous Reviews to Public Profiles: Users get "Glassdoored"

Glassdoor, traditionally a platform for anonymous employer reviews, has begun adding users' real names to profiles without their consent, utilizing public sources for identification. This change follows Glassdoor's acquisition of the professional networking app Fishbowl, which requires identity verification. Despite assurances of anonymity, this shift has raised data privacy concerns, with users like Monica discovering that opting out is not straightforward and could lead to potential retaliation from employers. The company's insistence on non-anonymity for profile names contradicts its previous policies and has led to user pushback and account deletions. Glassdoor defends its practices, emphasizing user options for anonymity while integrating Fishbowl features, but the blend of Glassdoor and Fishbowl data introduces legal and security risks for users, sparking debate over the platform's commitment to user privacy and anonymity.

Key Takeaways:

• Glassdoor has controversially started adding users' real names to their profiles without consent, citing identity verification needs following its acquisition of Fishbowl.
• Users face difficulties in opting out, risking exposure and retaliation from employers, contrary to Glassdoor's previous commitment to anonymity and privacy.
• Always treat information posted online as public. If you want it to stay private, keep it to yourself.

(Source: Ars Technica)

Microsoft's AI Strategy Intensifies with DeepMind and Inflection Talent

Microsoft has announced the appointment of Mustafa Suleyman, co-founder of the AI startup DeepMind acquired by Google in 2014, as the executive vice president and CEO of Microsoft AI, where he will spearhead the company's Copilot AI initiatives. Suleyman, who departed from Google's parent company Alphabet in 2022 to co-found Inflection AI, brings a wealth of experience in AI innovation and leadership. Joining him at Microsoft is Karén Simonyan, Inflection's co-founder and chief scientist, now appointed as chief scientist for Microsoft AI, along with several employees from the startup. This strategic move aims to bolster Microsoft's AI capabilities, particularly in enhancing its Copilot feature across various products like Bing and Windows. Satya Nadella, Microsoft's CEO, praised Suleyman's visionary leadership and pioneering spirit in a memo, highlighting the expected contributions to Microsoft's AI endeavors. Meanwhile, Demis Hassabis, Suleyman's fellow DeepMind co-founder, continues his role at Google DeepMind amidst Google's challenges with AI developments, including the recent controversies around its image-generation feature.

Key Takeaways:

• Mustafa Suleyman is appointed as CEO of Microsoft AI, bringing his AI expertise from DeepMind and Inflection AI to lead Copilot initiatives.Microsoft enhances its AI leadership by also recruiting Karén Simonyan and several Inflection AI employees, aiming to fortify its Copilot feature and other AI products.
• Structuring this as an "acqui-hire" enables Microsoft to reduce the risk of antitrust scrutiny and other complexities that could have come with purchasing Suleyman's company.
• Amidst Microsoft's strategic AI advancements, Google faces setbacks with its AI technologies, striving to overcome recent challenges in image-generation and chatbot functionalities.

(Source: CNBC) 

Empathy at $9/Hour: Nvidia's AI Agents Redefine Patient Interactions

Nvidia has partnered with Hippocratic AI to introduce AI-powered "empathetic health care agents" that surpass human nurses in efficiency and cost-effectiveness on video calls. These agents, leveraging Nvidia's technology and trained on Hippocratic AI's health care-focused LLM, aim to establish stronger human connections with patients through enhanced conversational reactions. Tested by over 1,000 nurses and 100 licensed physicians in the U.S., these bots have demonstrated superior performance across various metrics compared to both human nurses and other AI models. The collaboration highlights the potential of AI in addressing the health care worker shortage in the U.S., offering a cost-efficient alternative at $9 per hour, significantly lower than the median hourly rate of $39.05 for nurses. This development underscores the evolving role of AI in enhancing health care delivery and patient outcomes.

Key Takeaways:

• Nvidia and Hippocratic AI's collaboration introduces AI health care agents outperforming human nurses in effectiveness and empathy on video calls.
• The AI agents, costing $9 per hour, present a cost-effective solution to the health care worker shortage, contrasting with the higher hourly pay for nurses.
• Tested by health care professionals, these AI agents have outshined both their human and AI counterparts in various health care-related tasks, promising an innovative shift in patient care.
  

(Source: Fox Business)

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a GRC Strategist who is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else. This post was written with the assistance of an AI language model. The model provided suggestions and completions to help me write, but the final content and opinions are my own.