AI & Technology
Be Wary of Sycophantic Assistants -- The Next Platform Commoditization Breaker
All chat platforms and LLM tools have become commodified tasked with creating as much lock-in as possible for users. In general, most GenAI power users prefrer to flip their models as some are margianly better at some tasks than another – but on average, the capabilities are reaching parody.
As advertising and MCPs are designed to keep a user hooked in, using a single model that will benefit its parent company financially, more and more needs arise to create this lock-in, in order to build its user base and collect more training model data–thus, letting the training and experiences expand.
On the downside, a good number of users will be utilizing these tools for not only research, productivity, and automation tasks, but create the sycophancy illusion that these models are “alive” and show “emotion” to keep the non-tech enthused user also hooked on what a model has to offer. In this category, we have Mico – an assistant built into Microsoft’s CoPilot that’s designed to be its 2025 equivalent of Clippy that we all know and love from the 90s.
Mico is part of a Microsoft program dedicated to the idea that “technology should work in service of people,” Microsoft wrote. The company insists this effort is “not [about] chasing engagement or optimizing for screen time. We’re building AI that gets you back to your life. That deepens human connection.” - Ars Technica
LLMs are tools, and I worry about stories that some consumers are mis-utilizing these parasocial relationships giving them emotion, reason, and the illusion of relationships – whether that be true friendships or sometimes more.
[Microsoft] says it’s also working to evolve Copilot’s personality and tone, with the introduction of a new mode called “Real Talk.” This will allow the AI to mirror the user’s conversational style but won’t be as sycophantic as other AI assistants have been. Instead, Microsoft says that it will feel like something that’s “grounded in its own perspective,” and will push back and challenge your ideas, which could encourage you to see things from a different point of view. - Ars Technica
This attempt to break the parasocial bounds is something that must be welcomed, especially with a business forward facing product such as CoPilot. Microsoft’s goal should always be increasing productivity, a task that they’ve excelled at (no pun intended) over the past many decades with its Office and 365 incarnations.
With differentiation, it is important that each of these models and platforms do try to target different audiences with their needs. As Windows has its aim of becoming more agentic in nature moving forward, it seems more likely that Mico will be more integrated on that consumer level, between the OS, consumer portions of Microsoft 365, Xbox and other ecosystem products.
Even with the best of intentions, The Ars Technica article ends with the following salient point, one that I’ve been raising issue with here:
But adding a friendly, Pixar-like face to Copilot’s voice mode may make it much easier to be sucked into feeling like Copilot isn’t just a neural network but a real, caring personality—one you might even start thinking of the same way you’d think of the real loved ones in your life.
In the end, our attention is the commodity. Just as it was with social media and the app ecosystems, particular use cases of GenAI seem to be attempting to replace that. We have to be careful when interacting with these tools and try not to take our eye off the ball when it comes to creating productivity enhancements, not false relationships.
The Learning Curve of Agentic Browsing
With agentic browsers all the rage, it’s understandable that in these early days – it’s still confusing for the average consumer to unpack. in The Verge’s test with Opera’s Neon browser, the increased friction between tools makes such a product a burden for users. This isn’t to say that the technology is flawed, but early design and early days are its biggest issue.
As with other AI browsers, doing things with Do was also slower than doing it ourselves, though it hinted at what outsourcing the general mundanity of web surfing could look like. And using Do doesn’t mean you can completely check out just yet. Sometimes it encountered obstacles that only a human can handle. When it did, the Do tab at the top of the screen flashed in an easily missed shade of red letting us know we needed to step in and help the bot on its way.
The idea of handholding a tool through a process of thought or stream of tasks can still seem daunting. The consumer is often told that the browser can self-deal without much interaction from the user. We are not to this point as of yet, however, what better time than now to trial and error what this may look like in real-world practicality.
At times, using Neon felt a bit like working with a hapless intern we’d never asked for rather than a sophisticated, timesaving piece of technology. Often, one of its AI systems would ask for feedback, then just launch into a task without waiting for a response. Given its ability to use the browser, it’s all too easy to imagine where this proactivity could go very wrong, such as sending out a load of LinkedIn requests to people you had just wanted to anonymously stalk in a professional capacity.
In many cases, utilizing Generative AI in the workplace takes more time and tweaking than the user completing the task themselves. This is counterintuitive to the narrative that AI makes workflows and completing tasks easy and interoperable. What makes this even more an uphill sell for Opera, is that the Neon browsing product currently costs $20 per month – in its current shipping state.
Given many real world business applications, the jury is still out as to whether GenAI is becoming useful in the workplace, i.e. having to take more time to backtrack to check for accuracy, the proper workflow stream, and the correct results. Until that changes, as I’ve always believed, time and cost savings will not be realized for the everyday user and/or business productivity.
The Verge article concluded the following:
Neon feeling more like an AI browser we need to adapt to than a browser that’s smart enough to adapt to us.
Shoving tools into a browser creates overcomplication, slowdowns, and redundant features that can hinder use. It’s down to the fact that agentic browsing products still do not quite know what to do with themselves, but the fact they are present does not automatically mean cost and time savings are realized.
This is something important to watch as these products either evolve, or whether the browser goes away completely in favor of a new medium that directly puts user in touch with GenAI logic and reasoning.
Apple Loses More Talent to GenAI Firms
Apple continues an innovation brain drain with Siri, as Meta just recently hired Ke Yang to oversee the revamp of its lagging voice and GenAI assistant as rivals continue to topple it. Just a few weeks ago, Yang was tapped to run struggling Siri (including Apple Intelligence) and bring it up to par with other competitive products of its stature like Gemini, and ChatGPT.
The group is developing features to make the Siri voice assistant more ChatGPT-like by adding the ability to pull information from the web.
Yang was leading the Answers, Knowledge, and Information (AKI) team which was tasked with making Siri more GenAI like where an ‘answer engine’ was being created to more easily craw the internet for information.
In August, a report detailed that Apple assembled a new internal team, “Answers, Knowledge and Information,” to develop a ChatGPT-like search tool. The team operates under John Giannandrea, Apple’s current AI head. Robby Walker initially led the team before Ke Yang stepped in to take charge after his exit.
The setbacks continue as GenAI leaders such as OpenAI, Meta, and Anthropic are poaching talent from other firms who are currently behind in similar product enhancements. These outfits have been known for recently paying high dollar, high bonus figures to build out their own GenAI divisions to help differentiate themselves from other commodified products in the pack.
This isn’t the first time that Meta has been acquiring talent from Apple, as the AKI team has seen many departures within the past few months.
The Mark Zuckerberg-led company had poached top AI executives from the iPhone maker before, including Robby Walker and Ruoming Pang, as earlier reported by Bloomberg News.
Apple has yet to set aside portions of its vast balance sheet to developing GenAI products but rather is more interesting in utilizing Google’s Gemini as it already has Google Search as its default search engine and has for years. This development may not be as dire as it seems. It’s been much more conservative in its R&D as it seeks to develop more hardware products, which would give Google an upper hand in consolidating placement within the rumored smart display and robotics devices.
If we are in an AI bubble as Jeff Bezos and Sam Altman predict, the amount of investment will crater, creating a new playing field of only the strongest contenders. Apple would be wise to hold on to its vast balance sheet of roughly $40 billion of cash and cash equivalents to continue to product R&D.
The only component of GenAI that changes hands more than component deals is talent. Apple is not alone in this manner. All of the largest Fortune 500 company investors like Meta, Google, and Microsoft will purchase talent from acquihires and from the largest private firms like Anthropic and OpenAI.
This talent funnel goes both ways and has yet to show signs of slowing down, as each are attempting to find their way to the next big breakthrough in either agentics (MCP, etc…); or to break free out of the commodified LLM roadmaps they find themselves in.
Quick Hit: ChatGPT Allows Third-Party Tie-Ins
🧑💻 Platforms and ecosystems are everything. LLM products are no different. OpenAI’s ChatGPT is allowing apps like Zillow, Etsy, and Spotify to utilize its Model Context Protocol (MCP) APKs to tie-in to its product.
📱 The iPhone never really reached true market leadership position until the App Store came into fruition, or Google until the acquisition and implementation of DoubleClick.
🛜 As ChatGPT stands now, this is the next logical step in attempt to grow market share in its various business segments.
This was a quick hit for Linkedin commenting on the original post from Ars Technica.
The Infancy of Ecommerce Through Agentics Has Begun
🛍️ We are starting to see the beginnings of agentic ecommerce through OpenAI’s ChatGPT, according to The Wall Street Journal.
🛒 The US based trials are allowing users of Etsy and Shopify to utilize Instant Checkout, for single items only at this stage, but it is a bit of an evolution at this point – one that may grow into a multibillion-dollar industry if successful. This is certainly one development to watch.
🤖 The eventual automation of merchant protocols to payment systems must come together to make this sequence frictionless and proper security protocols must be put into place before moving this trial into a larger scale.
This quick hit was originally posted on LinkedIn.
The Latest in Gaming Consolidation: Electronic Arts
Yesterday, it was reported that a group of private equity investors including the Saudi Public Investment Fund, Jared Kushner, and Silver Lake were interesting in taking Electronic Arts (EA), private in a $50B transaction. EA had been struggling in recent years to find its footing when including a large amount of consolidation in that sector.
If you haven’t followed the industry, this is on the heels of Microsoft making large transactions in gaming with its purchase of Activision-Blizzard-King (ABK) a few years ago, which reached high levels of regulatory scrutiny due to fears of monopolistic practices. Mostly those fears are unwarranted as the software giant has been more than willing to put its previously Xbox-exclusive titles on rival platforms with Flight Simulator 2024 being the latest example.
The Saudi government and investment firms understand that its heavy reliance on the gas and oil industries are not going to last forever, hence the recent transactions across many different industries in an attempt to diversify its economy away from its primary natural resources. This isn’t the PIF’s first foray into the gaming sector. In 2022, it purchased a 5% stake in Nintendo, and Pokémon Go creator Niantic by way of Scopely for $4.9B about a year later.
Electronic Arts is mostly an annuity business with its EA Sports division regularly updating every year. If you’re a Madden or UFC fan, each edition is likely to be purchased. EA also has a mobile gaming business with The Sims and Bejeweled series of titles. Annuity businesses are great for a firm in general, but not the public markets – they expect continued growth with higher margins; something EA has been unable to do in recent years.
During COVID, like most of the technology sector, companies over-hired and invested as if stay-at-home would be a perpetual cycle. When that turned out not to be the case, massive scale backs in spending occurred, and massive layoffs ensued that are still happening today. As a natural result in public and private markets, consolidation ensued.
Some may argue that Microsoft overpaid for Activision-Blizzard for $75.4B, but I believe that will likely result in a write-down in coming quarters if not years. This transaction made it a platform maker rather than a pure-play console manufacture. EA doesn’t make consoles, but it could easily transition into a pure subscription service, furthering building out EA Play and growing its revenue and annuity business.
Given President Trump’s involvement with his son-in-law, Jared Kushner, and the Saudi government being primary purchasers in this deal, there should be no regulatory hurdles placed upon this transaction such as was the case with Microsoft and Activision Blizzard.
This is a trend that will continue as subscription services and mobile platforms are the future of gaming. I also would not be surprised if Apple embraces this route as it continues to grow its subscription business through mediums such as Apple TV hardware.
Nvidia and Intel -- There's Only One Winner
When considering Nvidia’s GPU and parallel computing dominance, it’s important to take a look at how it can capitalize on product growth of the GenAI era. Last week, Nvidia announced a deal that would invest $5 into flailing Intel – a move that is great for Intel in the short term, that can use all the funding it can get for survival, but it also may be a better contract for Nvidia, itself.
According to the terms of this deal, Intel will build Nvidia’s tech stack onto its current X68 architecture’s SoC, giving Nvidia an even stronger foothold outside the data center, mobile, manufacturing and vehicle. It’s worth mentioning too that AMD and Nvidia do have some overlap in competition that would only increase with this arrangement. According to Gizmodo:
Intel and Nvidia’s new buddy-buddy attitude may offer more competition for AMD, though it could take a different form than AMD’s all-in-one approach. We won’t know yet what variety of chimera chip this will eventually look like. In the Q&A, Huang said he hopes the partnership will “address a vast majority of the PC consumer notebook market.”
Nvidia, like all tech firms highly leveraged in one category, mainly the data center, it must diversify to keep the firm growing amidst the possibility of the AI bubble bursting. It’s no secret that Nvidia has wanted to enter the CPU market for some time, entrenching on a dominant Intel/AMD desktop and laptop majority sector. As ARM, the energy efficient, mobile first architecture is taking rapidly taking over this legacy and aging x86 architecture, it only makes sense for Nvidia to put its dominance to work in vertical sectors.
Given Intel’s struggling fabrication business, it makes sense for Nvidia to potentially take over this division and utilize it to manufacture both firm’s chips, obviously giving itself primary utilization since it would control a portion of Intel’s stake. Integrating efficient Nvidia technologies into inefficient and broken Intel processes, could fast-track the innovation Intel needs to abandon x68 and at last, properly move to ARM architecture.
With all of Intel’s short-comings as a firm, they still control over 80-percent of the market, which would allow Nvidia to gain a significant foothold by lending technologies to finally right-size the product line. Nvidia using Intel as a trojan horse into the dominant CPU market can only be a gain for Nvidia as it seeks to diversify but also leaving Intel no choice as it scrambles to seek investments from outside firms.
It’s too early to tell whether Nvidia will eventually acquire Intel all together, but if they are the one firm to truly right the ship at the legacy chipmaker, this $5 billion deal will seem like a bargain in only a few years. Given all the information we know at the moment, this is a win-win for Nvidia for all of the above reasons. At the very least, this small investment on Nvidia’s part could change the industry as we know it.
ASML's Big GenAI Investment in Mistral
Dutch semiconductor tooling supplier, ASML announced that the firm is investing $1.5 billion in the French GenAI company, Mistral. As a result, ASML will have gain a board seat. When this new investment is factored in, Mistral may now be worth $11.7 billion. According to Seeking Alpha:
Mistral was valued at more than $6 billion after its Series B round last year. Reports in recent weeks have suggested the latest financing could lift its valuation as high as $14 billion.
So, why is this happening? ASML makes extreme ultraviolet lithography (EUV) technology that goes into producing most modern, smaller fabricated chips for customers as TSMC, Samsung, Nvidia, and other top chip makers in the modern AI data center arena. Like most business strategies, the investment could (and likely is) multifaceted.
It could be that ASML wants to be in more control of its end-to-end verticals–that is what the end customers are doing. ASML does not make chips themselves but think of them as the company that makes the tools that makes the chips, that go into the data centers, that support GenAI firms.
We can also consider due to American-led tariffs, especially on semiconductors, that ASML wants to bring European tech assets under more control to shorten the supply chain between them. Domestic politics within the EU also make this an interesting play.
European customers are keener on keeping their own data away from American or Chinese servers, so this allows more data sovereignty to appease regulators and comfort Mistral’s customer base. In addition, it could just be a diversified investment opportunity. Nvidia already put a $6 billion investment into Mistral some time ago.
Lastly, Mistral itself, could provide useful data back to the original supplier about how better to serve its semiconductor and to an extent, endpoint GenAI customers to make improved technologies, understand what these biggest customers and consumers of data centers ultimately require, and crate efficiencies in the total supply chain where needed.
Energy consumption and data center costs are two headwinds currently amplified when making infrastructure buildout to support the ever-growing demand of GenAI firms. Technology firms have always thrived on ecosystem development. This would go a long way in building out those systems to keep Mistral competitive in this environment.
Have My Agents Talk to Your Agents
Last week, Atlassian, the SaaS company that owns such products as Jira, Confluence, and Trello announced that it would be purchasing The Browser Company, whose products are Arc and now the Dia browser for $610 million in cash, and would remain independent of the parent company (which normally doesn’t last for long). It’s notable on top of the news that in an about face for an antitrust ruling, a judge ruled that Google would not have to divest itself of Chrome as a potential monopolistic remedy.
We’ve seen the term “agentic” thrown around a lot, so here’s how IBM defines it:
Unlike traditional AI models, which operate within predefined constraints and require human intervention, agentic AI exhibits autonomy, goal-driven behavior and adaptability. The term “agentic” refers to these models’ agency, or, their capacity to act independently and purposefully.
Browsers are big deals once again, after becoming stale in innovation when adding in the great AI experiment. Perplexity unveiled its Comet browser which is an AI first product not too long ago as well. This is all about agentics, the current and next phase of GenAI products and business verticals. Google has already integrated Gemini into Chrome, Microsoft integrates Copilot into Edge, and so on. This is only the start of this new phase.
No longer does a user browse the web to find information. These agents can act on your behalf to be more productive and attempt to increase productivity. They are able to complete tasks on the user’s behalf such as keeping track of a target price of a consumer product, then venturing out to purchase it when it gets into a defined range utilizing various hooks or APIs where agent to agent communication takes place.
TechTarget lists some business use cases for this tool. One of them I want to highlight is call centers, for example:
AI agents in call centers orchestrate intelligence and automation across the multiple activities involved in serving customers, Brown explained. An agent might simultaneously analyze customer sentiment, review order history, access company policies and respond to customer needs based on those elements.
Using this example, we might see why Atlassian was interested in such an agentic browser product – streamlining its products into an enterprise tool that can work across workstreams, departmental silos, and from a business retention standpoint (lock-in) to their products so it’s harder for a business to migrate to competing tools.
Multiagent use cases can also work on behalf of the consumer. Tools exist today where users can check for the best prices and get alerts on flights, hotel, rental cars, durable goods, etc… The next stage will be these agents going out (on your behalf) to other agents to make a purchase and have it automatically book these travel criterias.
There should be a saying, “have my agents talk to your agents”, and we wouldn’t be far off of where the next phase of GenAI will lead us. Everything from SEO, marketing, and human interaction will change as a result and will have to adapt to these circumstances, as they have with any new implementation or evolution of technology.
A Quick Note on "Apple in China" by Patrick McGee
Finished reading: Apple in China by Patrick McGee 📚
📚 After reading “Apple in China” by Patrick McGee, it was reiterated why Apple slowing moving manufacturing to low-cost contract manufacturers like Foxconn and Pegatron over decades, competed on low to zero margin businesses – just to gain the competitive advantage and knowledge of how to produce such complex products themselves.
🏭 This how Chinese firms such as Huawei and Xiaomi were able to make better phones at lower costs, and how BYD was able to pivot to EVs in such a quicker and more innovative fashion.
📱 Apple taught the Chinese government and assemblers (a little too well) about the manufacturing process, thus allowing them to compete on the global stage to grab footholds in Europe, the Middle East and Africa with much better products, capabilities and price-points.
✅ It was a wonderful read if you’re into technology, supply chains, and long-term geopolitical consequences. I highly recommend this read.
WSJ Study on Career Skill Certificates
Job skill certificates from the likes of Coursera or edX are exactly what you make of them. They are a jumping off point for learning new skills and techniques that can be put forward in the workforce. A recent WSJ article cast doubt on their validity and career advancements that they claim to skill-up for.
While I disagree that they should be the end all be all requirement for an employer to make decisions on a candidate – they can provide must more value that one might think. Intrigue and curiosity are the main drivers why a prospective employee may try to take one of these credentialed courses or professional certifications. It’s meant as a stepping off point in order to build upon that knowledge. It’s not what they’re doing in the course, it’s what comes after.
The credentials with the best outcomes made a difference: Workers who received one of the 2,000 top-performing credentials earned about $5,000 extra a year, on average, within 12 months of completing the programs. Many of the certificates were in nursing, radiology and other medical fields—where credentials are widely valued by employers and labor is consistently in demand.
That is the issue with his study – what’s in demand will always change. What was data analytics and coding yesterday, will be something completely different tomorrow.
Let’s take the example of the role of a Business Analyst, for example. Coursera has a wonderful program called “Microsoft Business Analyst Professional Certificate”. The idea is to take someone from the fundamentals to a working project at the end to prove their knowledge retention and introduce knowledge workers to the skills that the software company has to offer. If you’re new to Power BI, Power Apps, and the Power Platform in general, than this is a great introduction that weaves these concepts into a curriculum.
Like all skills and experience, nobody can be an expert from one pass through of this course, but what it does is lay the foundation to garner an introduction to the company’s products which are widely used in many industries. It’s not limiting to a single platform, but the concepts can be taught to many competitors products (i.e. if you understand how to use Power BI, then Salesforce’s Tableau will be understood just as easily).
Upon competition of the course, Microsoft offers a voucher for half-off the price of the entry level Power Platform certification. While the merits of the study from The Burning Glass Institute and the American Enterprise Insitute need to be delved in further, this conclusion is not a one-size fits all study. Many of us pivot careers every 2 to 5 years in today’s information economy. It’s likely that you need to reskill and retool yourself before then. Skill certificates have been always a great introduction to a new topic and interests, and they will continue to provide that crucial role in the future.
Finished reading: Zillow Talk by Spencer Rascoff 📚
MIT Technology Review Comment: Don't Ban ChatGPT in Education
Like all new technologies in education, the initial response is to ban them. Consider Wikipedia, for example. Over a decade ago, the resource was chastised for the chance that a student may plagiarize an entry. On the contrary, it’s become a well sourced tool for initial research on a subject, with well sourced citations.
Fast forward to today – LLMs are tools to be used in critiquing arguments, the creation of ideas, and a second opinion to inform the writer or reader of salient points that may have been missed. Never truly trust a technology on face value, but proper use cases must be taught (by faculty and parents) or students will fall behind.
My comment was originally posted for LinkedIn.
Knowing Your Workflow for Note Taking
🔖 In my quest to become more knowledgeable in topics and subjects that are either relevant to me or my career, I like to use tools such as Obsidian and Google Keep to just down notes and reflections.
📗 In conjunction with my routine of ingesting insightful blogs and journalism, I’ll peruse Reddit (for example) to brainstorm blog ideas or retaining useful facts to whatever project I’m considering. When following the appropriate subreddits, consider the comments as a way to consider others' opinions to challenge your own. Lastly, I will synthesize it for later use.
🧠 Personal Knowledge Management, or PKM, is only becoming more important in the age of GenAI (filtering LLM considerations from original sourcing). I have a lot of work to do in this area, but it takes practice to grasp a workflow that works for you and your needs.
Making Siri Great Again
If true, this Bloomberg report would be one of those rare instances that Apple would admit defeat – at least for the time being. Partnering with OpenAI or Anthropic for Siri may buy them some time. Then again, it could be analogous to Apple ceding the ad market, which is why they claim to be ‘privacy first’.
In recent weeks, it has been circulated that many firms have been interested in Anthropic such as Meta and Apple itself. If Meta were to be successful, they would gain valuable real estate on the MacOS and iOS platforms, likely ending Google’s multi billion dollar a year contract for search.
This would also confirm that Apple was unable to purchase the company, thus, moving to the next best thing – a partnership that would vastly boost Anthropic’s already sky-high evaluation.
In the past few weeks, OpenAI has not expressed its feelings with Microsoft as positive, so a decoupling from the software giant would result in new revenues from Apple. Nobody ever went broke from diversification, which includes the customer base.
I Have LLMs Critique My Writings and Posts
Continuing on the theme of LLMs enhancing your own work rather than replacing it. I had several platforms sift through and critique my writings on my posts and blogs. Some of the results were interesting, and unexpected to say the least. For this test I prompted Gemini 2.5 and Claude Sonnet 4 the following: “Critique the writings of michaelmartinez.co.”
This is yet another tool in my workflow. I could take or leave the suggestions, but as always, it’s an option. After reading through the “experiment” I want to know what you – the reader would like to see more of from me in future posts and writings.
Gemini 2.5 talked of the following strengths:
Breadth of Knowledge: Martinez exhibits a wide array of interests, seamlessly transitioning between discussions on cybersecurity, the nuances of digital advertising antitrust cases, and historical analyses of xenophobia. This breadth enriches his perspectives and allows for interdisciplinary connections.
Topical Relevance: His chosen subjects are highly relevant to current global discourse, addressing pressing concerns in the tech industry (LLMs, AI, antitrust) and societal issues (xenophobia, foreign policy).
Clear and Concise Communication: The articles are structured well, with clear headings and a direct writing style, making complex topics accessible to a broad audience. He effectively summarizes key points and arguments.
Thought-Provoking Insights: Martinez often delves beyond surface-level observations, offering insightful critiques and raising pertinent questions, such as the effectiveness of breaking up large tech companies and the future impact of AI on advertising. His willingness to express concern about negative rhetoric and connect it to historical patterns of xenophobia adds a moral and ethical dimension to his foreign policy discussions.
Personal and Reflective Tone: Elements like his “Reading Updates” and experiences with Micro.blog add a personal touch, making his content more relatable and authentic. His emphasis on continuous learning and reading widely underscores a commitment to self-improvement and intellectual growth.
Use of External References: He frequently references external sources, such as TechCrunch’s “Cyber Glossary,” Jesen Huang’s views on AI, Mark Gurman’s criticisms of Apple, and Clayton Christensen’s “The Innovator’s Dilemma.” This demonstrates research and supports his arguments with credible insights.
The second part of the output were the “Areas for Potential Enhancement”.
Deeper Dive into Specific Arguments: While he touches on various aspects of each topic, providing more in-depth analysis or expanding on specific arguments with additional evidence or case studies could further strengthen his positions.
Original Research or Unique Perspectives: While he synthesizes information effectively, incorporating more original research, unique data points, or highly distinctive viewpoints could elevate his critiques to a more authoritative level.
Engagement with Counterarguments: Presenting and directly addressing potential counterarguments to his positions could lead to more robust and nuanced discussions.
Claude provided me with almost the same strengths and weaknesses as the Gemini prompt but went further in two ways. First, is a “Content Assessment”.
Technology Commentary: His AI/LLM analysis is generally sound but not groundbreaking. He correctly identifies key limitations but doesn’t offer particularly novel solutions or frameworks for thinking about these issues.
Political Commentary: His piece on American xenophobia attempts to draw historical parallels between treatment of Japanese Americans, Muslims post-9/11, Russians during the Ukraine conflict, and current Latino deportations. While the historical connections are valid, the analysis lacks nuance and depth that such complex topics deserve.
Educational Insights: His observations about AI in education are practical and well-reasoned, particularly his emphasis on teaching critical thinking alongside AI literacy.
Lastly, Claude provided an “Overall Assessment”.
Martinez’s blog represents competent but not exceptional commentary on technology and society. His strength lies in providing accessible, practical perspectives on complex topics, particularly around AI adoption and digital literacy. However, the writing lacks the depth of analysis or original insight that would distinguish it in a crowded field of tech commentary.
The blog serves its apparent purpose as a personal platform for sharing thoughts and maintaining an online presence, but it doesn’t rise to the level of must-read commentary on the topics it covers. For readers seeking practical, moderate perspectives on AI and technology adoption, it offers value. For those looking for cutting-edge analysis or original research, they would likely need to look elsewhere.>The author’s commitment to continuous learning and reading is admirable and likely keeps his commentary reasonably well-informed but translating that input into more distinctive analytical output would strengthen the overall impact of his writing.
I will keep retooling and refining my methods in the future based on this feedback. What do you, a human, think of the assessments from two of the biggest GenAI tools out there?
GenAI is Still Not Replacing You
Back in 2023, when LLMs and GenAI was still in its infancy, I argued that GenAI will be a tool for those in the job market and change the workflow of the way we spend our careers. In the time since I wrote that piece, not much has changed and I still stand behind the rationale.
It is essential to clarify that LLMs, including GPT-4, are not true AI. Despite their impressive capabilities, they lack true understanding, consciousness, and self-awareness. LLMs rely on pattern recognition and statistical processing rather than genuine cognitive reasoning. They do not possess subjective experiences or emotions. They are tools designed to process and generate text based on patterns learned from vast amounts of data. Therefore, LLMs cannot fully replicate the complexities of human intelligence, nor replace the multifaceted skills that humans bring to the workforce.
The core to my argument is the lack of reasoning and thinking. To this day, I do not “like” those terms and believe we should choose better words to describe the tokenization aspects of it all.
Recently, The Economist published a piece entitled, “Why AI hasn’t taken your job”. It takes the argument that AI has changed the nature of some careers such as those in translation (See Duolingo) and learning, but postulates that upskilled careers such as interpretation of language learning has increased. Upskilling and upshifting of productivity are still key to future successes in sectors such as this.
Klarna is also given as an example where a choice is given between GenAI based customer service or a human:
“There will always be a human if you want,” Sebastian Siemiatkowski, its boss, has recently said.
More importantly (nothing is definite with new technologies), given the massive technology layoffs with claims that AI is replacing work by CEO’s, the data tells a different story.
Across the board, American unemployment remains low, at 4.2%. Wage growth is still reasonably strong, which is difficult to square with the notion that AI is causing demand for labour to fall. Trends outside America point in a similar direction. Earnings growth in much of the rich world, including Britain, the euro area and Japan, is strong. In 2024 the employment rate of the OECD club of rich countries, describing the share of working-age people who are actually in a job, hit an all-time high.
The conclusions are the same – GenAI replaces redundancy and not people. As the technology matures, it may change if new unforeseen breakthroughs were to surface, but as of now it’s still best to teach yourself how to use these tools so that you aren’t replaced by an employee who is already familiarized with it.
AI and Learning: There's a Major Disconnect Occurring in Education
Just like with all industries and applications, the use of LLMs is literally rewriting all of the best practices with education currently being the largest social sector being disrupted at the moment. Rather than using LLMs to ‘cheat’, educators and public administrators must teach students how to use and coexist with them rather than relying solely on them.
A lot of students have abandoned critical thinking all together and resulted in outsourcing all of their knowledge to these LLMs just to make answers and save time without learning or even conducting reasoning of their own to consider what the prompts are or what they’re telling them. As a result, teachers, administrators, and parents are beyond frustrated and returning to the good old blue books as cited by this Gizmodo article.
Students need to learn how to properly research while understanding proper time management. I won’t say laziness is at work on the part of all parties involved, but the quickest way to get from A to B is often using tools at your disposal – this is true in education or eventually the workplace, however, a lot is lost in this process including how to critically think about what output LLMs are displaying or what it might mean for the overall context of the subject.
Education has always been a lagging indicator of technological trends, and this is no different. LLMs and other types of GenAI are tools, not the end all be all solution in the classroom. Using it as a partner in research yet taking a critical view of what it’s telling you is paramount to making research easier for all, without compromising the time-honored tradition of writing research papers and a child’s knowledge retention.
A full education, as always, should concentrate on a child’s soft-skills – learning how to critically think, put together proper research, how to write for life, and home in on communication skills to make them successes in their careers and lives. Tools can do that, pouring prompts into an unchecked LLM cannot.
Google's Gemini will Contain Ads -- It's Only a Matter of Time
It’s common knowledge that Google is an advertising company first and foremost. All of the products weave together this ad network that a lot of governments and organizations consider to be anti-competitive. If you query a standard Google search, you’re starting with sponsored posts, followed by more advertising – which can be hard to navigate when you need accurate and actionable information fast.
Gemini, Google’s AI and LLM platform is just that. It’s a tool for consumers and businesses alike, which can be marketer’s dream. Recently, it was announced that marketers can use the service to insert more strategic ad placement into YouTube. The use of agentics, that is, using GenAI on your behalf to make decisions, automate decision making based on the user’s parameters, and adaptability – is now becoming commonplace among browsers, LLMs, and other AI tools and infrastructure. Marketing and advertising firms will have to adapt to serve these minimally invasive asks with minimal human intervention. The trick is serving ads through these means.
In the first paragraph, I’ll reiterate that Google is an advertising company, thus this is just one more avenue they must figure out to use its closed ad-network to bring in more revenues. They must walk a tight rope though due to antitrust concerns currently before the US federal government and EU agencies. While the early 2000s was dominated by SEO; GEO (Generative Engine Optimization) is firstly built to be utilized properly on AI platforms.
Anthropic recently announced that Reed Hastings, founder of Netflix has joined their Board of Directors. This may seem strange on the surface but makes perfect sense when we realize that Netflix has a robust advertising platform as the world’s top streamer. Hastings expertise in this arena will fit in perfectly to what Anthropic wants to pursue – becoming its own advertising platform to rival that of Google, which is no surprise given if the courts rule that Google has to divest Chrome; that Anthropic was a party interesting in purchasing it.
Google’s strategy has always been that of the tech industry as a whole; gaining as many users as possible with a new product, then turn on the spicket of advertising. We can only hope that the sheer number of ads inserted won’t damage the Gemini product as it has Google search. We might not need a government to dismantle the firm, the vast competition within the LLM space and all tech wanting a piece of the pie may force them to retool to strike a balance between users and AdSense. Thus, Google wielding its vast ad network to other products might become a coherent strategy – much as Microsoft focused on cloud rather than Windows throughout the 2010’s.
The Electric Vehicle Imbalance: East vs. West
As United States' EV tax credits have faded away into nothing, other regions such as the EU and China have doubled down on adoption because it’s what their consumers want. Domestics such as GM and Ford have failed to make compelling vehicles at appropriate price ranges with appropriate charging ranges.
Right now, domestic Chinese manufacturers such as BYD and Xiaomi are currently highly tarffied and unlikely to gain much traction in the United States market, however, since the ending of the $7,500 tax credits, more Americans are interested in these foreign auto companies.
When we think about it, the $7,500 credit was almost enough to cover BYD’s Seagull EV which cost roughly $10,000 USD and ranges 252 miles per charge. This is almost an embarrassment to American and Japanese makers as they can provide better range at a fifth of the cost.
For now, there is a major setback in North American adoption of EVs as the tax credits end, and EVs now cost over $50,000 as a result, however, momentum cannot be stopped. Trends tend to go parabolic in the medium-term, yet this adoption is still in the very early innings in the west. This is true with all forms of renewables including solar and wind. The current US Administration is attempting to kill any of this momentum – but with little affect. These trends transcend policy.
There is worry about Chinese manufactures and privacy from a United States standpoint, but Tesla is no different. Musk has falsely marked Tesla as full self-driving (FSD) when it is not, and current owners are locked in a class action lawsuit with the company. Tik-Tok is included in a lot of these foreign vehicles, but we also consider the unstable xAI is becoming integrated into Tesla models. It’s all about what and where the consumer would like to offload their privacy to. China and American privacy policies are no different in this day in age.
It’s been shown that the American domestic automaker has been unable or unwilling to provide meaningful change, yet most foreign automakers have been all too keen on delivering these inexpensive, yet innovative vehicles to the rest of the world. In order to modernize the electric grid, these products must also implement bidirectional charging – that is, charging back to the grid during the peak in order to balance the loads within the electric system.
North American auto makers are having a hard time innovating and growing like their international counterparts, but there is some hope. Ford, for example, has announced an entirely new manufacturing platform which lowers costs and increases range on new models, especially for a new 2027 model pickup truck. Time will only tell whether this is too little, too late, or yet another paradigm shift in the industry.