Business & Finance
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 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.
Finished reading: Zillow Talk by Spencer Rascoff 📚
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.
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.
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.
Google & Meta Share a Common Antitrust Thread: Advertising
Google and Meta have come under vast amounts of antitrust scrutiny over the past few years, especially in the US and the EU. It’s important to consider that both firms have more in common than one might think – they are advertising companies.
Regulators have been targeting both companies for alleging abusing monopolistic power in search, for Google, and Meta’s streamlining of properties (i.e. Instagram, WhatsApp, Facebook) to shunt competition. A lot of what’s been missing is the thread that puts their properties together. That would be their respective ad products.
The Verge reported that, “Judge Brinkema found Google “liable under Sections 1 and 2 of the Sherman Act” due to its practices in the ad tech tool and exchange spaces but dismissed the argument that Google had operated a monopoly in ad networks.” In a separate, but previous ruling last year, the courts ruled that Google must break apart properties such as Chrome. By itself, Chrome, YouTube, Android, Gemini, search and more are not the issue; but rather the ad platforms moving through them create a monopoly in the revenue generated in the ad market for which Google owns both the buy and sell side of their advertising exchange.
Separating Chrome out itself, won’t be much of an issue if there are no restraints in Google just forking a version of Chromium, which Chrome is based upon, and creating a new browser. Regardless, Google will still retain its monopoly stemming from their acquisition of DoubleClick which occurred back in 2008. If the DOJ wants to remedy the monopoly, it should look at remediation of controlling both the buy and sell side of the digital advertising economy. In recent years, Google has attempted to diversify their revenues away from majority advertising revenue into other businesses such as its cloud offerings, and acquiring Wiz – a large cloud security firm for $32 billion.
Meta
Now we move on to Meta. Just today, the company announced that its Threads platform will begin offering advertising in a limited capacity, likely to expand just as all other Meta properties do. Like Google, Meta is not immune to litigation. This morning, the EU fined both Apple and Meta for antitrust as well, in a long line of fines for violating the Digital Markets Act (DMA). The European Commission’s issue is one of privacy and violating the “pay or consent” model (using your data without permission and replacing the ad business with a paid version of these services). Like Google, Meta has heavily invested into AI and the metaverse as likely diversification ideas.
Remedies
In many of these cases brought on by the European Commission and the US DOJ and State AGs, the suggested remedy is to break up Alphabet (Google) and Meta into their individual parts. If this were the case, the ad businesses must go along with them. The more properties Google and Meta own and create, the deeper the ad network and revenue. OpenAI has already suggested that it would purchase Chrome from Google should that be the case. But it just creates another problem – another massive tech conglomerate, giving traditional search from Google, a run for its money, like OpenAI, would simply replace the juggernaut with itself. The Sherman Antitrust Act of 1890 has been cited as precedent for the potential breakups, however, this is dated legislation that was passed to deal with Standard Oil and AT&T of the times, not modern big tech.
What’s Next?
Both companies have stated that they will appeal these rulings, and any final decisions will likely take years. In the fast pace that technology moves, we must ask if these two firms will still look and act the same in a 2-to-5-year timeframe? Google’s Gemini and Meta’s Llama LLM’s and AI R&D will rapidly change in just the next 3 months if we can apply recent AI growth trajectories to them.
Like before, Google and Meta will be pressured to monetize AI in a changing landscape where traditional search is upended by agentics. What would current ad networks look like across LLM’s? That is a discussion for later down the road once methodologies are tested.
A Quick Conversation about Apple's AI & Siri Problem
In the technology sector, if you aren’t innovating, you’re falling behind. This is no different for Apple, who is not used to being behind on features. Generally, Apple waits until they’ve perfected a technology before introducing it to the public. Recently, this isn’t the case when we consider the cutbacks of the Apple Vision Pro, and this past week, AI features.
Famous Apple watcher, Mark Gurman, who is usually correct on Apple predictions published a scathing blog post about Apple falling behind with respect to LLMs and AI as a whole in his Daring Fireball post entitled, “Something is Rotten in the State of Cupertino”.
In his post, Gurman discusses how the promises that Apple announced has hurt the company’s credibility with customers. Siri has always been flawed without much innovation in the past few years, but with Google, OpenAI, and others surging ahead – Apple is left with what he calls Siri’s capabilities as “vaporware”.
In previous iOS updates, Apple had to deprecate and continually delay features because of bugs, AI hallucinations, and parlor tricks with non-differentiating features than that of say Gemini for Google or Claude for Anthropic. Voice assistants are as complex and innovative as ever, and now we’re witnessing the unfolding of what agentic browsers can accomplish.
In a recent blog post, venture capitalist, Om Malik, a legend in his own right, postulates that, “Apple has its own golden handcuffs. It’s a company weighted down by its own market capitalization and what stock market expects from it.”
This reminds me of the best-selling book by Clayton Christensen called, “The Innovator’s Dilemma”. The theory holds that current dominant companies fail to adapt to newer disruptive technologies (AI and LLMs in this case) and failing to pivot from their own strengths and ultimately fail. We see such a case with Intel, missing the mobile generation and ultimately at a crossroads of failure or being broken up and sold for pieces.
As we know, Apple has successfully broken the innovator’s dilemma before with deprecating its successful iPod for the iPhone, eventually releasing the iPad, and creating an ecosystem around which make the company increasingly successful with each pivot. It’s too soon to tell if Apple has reached its peak with major setbacks with Siri and Apple Intelligence, but it is alarming to shareholders and Apple stakeholders alike. It’s certainly a development to watch.
The Strategic Shift: Why UPS is Rethinking its Amazon Partnership and What it Means for Last-Mile Delivery
We’re well in the middle of earnings season, but something stood out to me regarding a firm in particular. UPS revealed a significant shift in its strategy: a reduction in its delivery volume for Amazon by 50% by the end of next year. This move, while surprising to some, is a calculated step aimed at improving UPS’s profitability and streamlining its operations. Let’s delve into the reasons behind this decision and what it means for the future of last-mile delivery.
While Amazon is UPS’s largest customer, accounting for almost 12% of its revenue in 2024, the company believes that reducing its reliance on the e-commerce giant will ultimately benefit its bottom line. UPS is aiming to shift toward more profitable endeavors. This strategic pivot is crucial for enhancing UPS’s margins, which refers to the profit margin, the percentage of revenue a company keeps after subtracting its costs.
About the Change
UPS’s decision also comes amid a larger company-wide transformation The company is reconfiguring its U.S. network and launching multi-year “efficiency reimagined” initiatives to save approximately $1.0 billion through an end-to-end process redesign. This includes an initiative to insource 100% of its UPS SurePost product. These initiatives are designed to make UPS a more profitable, agile, and differentiated company.
It’s All About Last Mile
The term “last mile” refers to the final leg of a shipment’s journey from a transportation hub to the end-user’s final destination. It’s often the most complex, time-consuming, and expensive part of the shipping process. Last-mile logistics costs can be substantial – sometimes more than 50 percent of total shipping costs. Several factors contribute to these costs, including labor costs, route optimization, fleet costs, warehousing, proximity of the delivery points to the warehouse, itself, the locations, and the number of deliveries along a route.
UPS’s move to reduce Amazon deliveries is likely connected to a desire to optimize its last-mile operations and cut costs. By reducing its reliance on one large customer, UPS can gain more control over its delivery network and potentially improve its efficiency and profitability.
UPS’s Financial Performance
UPS’s fourth-quarter 2024 results show a consolidated revenue of $25.3 billion, a 1.5% increase compared to the same period last year. The company’s diluted earnings per share were $2.01, with non-GAAP adjusted diluted earnings per share at $2.75, an 11.3% increase from the previous year. These results indicate a strong financial position. UPS expects 2025 revenue to be approximately $89 billion, with an operating margin of about 10.8%.
The Future
UPS’s decision to reduce its Amazon delivery volume is a strategic move to focus on more profitable projects and enhance its operational efficiency. By optimizing its network and streamlining its last-mile deliveries, UPS is positioning itself for sustainable growth and increased profitability. This shift underscores the importance of managing last-mile logistics effectively in today’s competitive market, where efficiency and customer satisfaction are paramount.
UPS' Q4 earnings report and press release can be found here.
DeepSeek's Surprise Entrance into the AI Arena
DeepSeek, a Chinese AI startup, has rapidly become a major disruptor in the AI landscape with its new AI model, R1. This model has gained global attention for its ability to compete with models like OpenAI’s ChatGPT, but at a significantly lower cost. The emergence of DeepSeek has caused ripples across the tech industry, impacting stock markets and sparking debates about data privacy and the future of AI development.
DeepSeek was founded in mid-2023 by Liang Wenfeng, a Chinese hedge fund manager. The company’s AI model, DeepSeek R1, was released on January 20, 2025, and quickly gained popularity. DeepSeek is an open-source large language model that uses a method called “inference-time computing,” which activates only the most relevant parts of the model for each query, saving money and computational power.
This efficiency has enabled DeepSeek to achieve comparable results to other AI models at a much lower cost. The company reportedly only spent $6 million to develop its model, compared to the hundreds of billions being invested by major US tech companies. Nvidia has described DeepSeek’s technology as an “excellent AI advancement,” showcasing the potential of “test-time scaling”. It was developed using a stockpile of Nvidia A100 chips, which are now banned from export to China.
DeepSeek’s emergence has led to a significant drop in the stock prices of major tech companies, including Nvidia and ASML. Nvidia suffered its largest ever one-day market value loss, shedding $600 billion. This has led investors to question whether the market is overvaluing AI stocks. However, some analysts believe this is an overreaction, noting the continued enormous demand for AI. DeepSeek’s ability to achieve high performance at low costs has raised questions about the massive investments being made by U.S. tech companies in AI. Some analysts believe DeepSeek’s efficiency could drive more AI adoption.
OpenAI has accused DeepSeek of using its models illegally to train its own model. There are reports that DeepSeek may have used a technique called “distillation,” to achieve similar results to OpenAI’s model at a lower cost. DeepSeek has also experienced security breaches, exposing over a million user chat logs, API keys, and internal infrastructure details. Additionally, the company’s privacy policy states that it stores user data, including chat histories, on servers in China. These security and privacy concerns have led to the US Navy banning its use.
The rise of DeepSeek has highlighted the limitations of US sanctions on Chinese technology, with some experts suggesting that the sanctions may have unintentionally fueled domestic innovation in China. President Trump has called DeepSeek’s launch a “wake-up call” for US companies.
DeepSeek’s R1 model is capable of answering questions and generating code, performing comparably to the top AI models. However, it has faced criticism for sometimes identifying as ChatGPT. The DeepSeek AI app is available on Apple’s App Store and online, and it is free. However, the company has had to pause new user registrations due to “large-scale malicious attacks”. Due to privacy concerns, some users are exploring alternative ways to access DeepSeek, such as through Perplexity AI or by using virtual machines. Perplexity AI offers DeepSeek on its web and iOS apps, although with usage limits.
The DeepSeek story is still unfolding, with debates continuing about its security, ethical, and intellectual property implications. While some are skeptical of its longevity, especially in the US market, DeepSeek’s emergence has undoubtedly had a major impact on the tech landscape and has forced the AI sector to re-evaluate its strategies and investments.
Works Consulted:
“DeepSeek Exposes Database with Over 1 Million Chat Records.” BleepingComputer, 30 Jan. 2025, www.bleepingcomputer.com/news/secu…
Wilson, Mark, et al. “DeepSeek Live – All the Latest News as OpenAI Reportedly Says New ChatGPT Rival Used Its Model.” TechRadar, 30 Jan. 2025, www.techradar.com/news/deep…
Laidley, Colin. “What We Learned About the Future of AI from Microsoft, Meta Earnings.” Investopedia, 30 Jan. 2025, www.investopedia.com/what-we-l…
Picchi, Aimee. “What Is DeepSeek, and Why Is It Causing Nvidia and Other Stocks to Slump?” CBS News, 28 Jan. 2025, www.cbsnews.com/news/deep…
LLMs will Augment Employment; Not End it.
LLMs, such as GPT-3.5 & 4 developed by OpenAI, possess impressive language processing capabilities. However, despite their remarkable abilities, LLMs are not poised to replace human workers. In this blog post, we will explore how LLMs will augment employment rather than supplant it, providing evidence to support this claim.
Contrary to the doomsday predictions of job losses due to automation, LLMs are not designed to replace human workers entirely. These machines excel at processing and generating human-like text, but they lack the cognitive abilities, creativity, and emotional intelligence that make human workers invaluable. LLMs are tools that enhance human productivity rather than replace it. They can assist employees by automating routine and time-consuming tasks, enabling humans to focus on complex decision-making, critical thinking, and creativity.
While LLMs can generate vast amounts of information, fact-checking remains a critical aspect of responsible information dissemination. Although LLMs have been trained on vast datasets, they lack the discernment required to verify the accuracy of the information they generate. Human fact-checkers play a vital role in scrutinizing and verifying the content produced by LLMs, ensuring that only accurate and reliable information reaches the public. Their expertise and critical thinking skills cannot be replaced by machines, making human intervention indispensable in the fact-checking process.
LLMs excel at automating mundane and repetitive tasks, freeing employees from time-consuming activities and allowing them to focus on higher-value work. For example, in content creation, LLMs can assist in generating first drafts, gathering research, or providing suggestions, saving valuable time for human writers who can then focus on refining, adding personal insights, and injecting creativity into their work. This symbiotic relationship between LLMs and human workers increases efficiency, productivity, and overall job satisfaction.
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 emergence of LLMs presents a promising future for the augmentation of employment rather than its replacement. LLMs will not replace human workers but will instead enhance their productivity and free them from mundane tasks. Fact-checkers remain indispensable in ensuring the accuracy and reliability of information generated by LLMs. It is crucial to remember that LLMs are not true AI; they lack the comprehensive cognitive abilities and emotional intelligence that make humans uniquely valuable in the workforce.
As we move forward into an era where LLMs become increasingly integrated into our lives, it is crucial to embrace their potential while acknowledging their limitations. By working alongside LLMs, humans can utilize the benefits of automation, focus on higher-value work, and tap into their unparalleled ability to think critically, be creative, and empathize with others. The key lies in understanding that LLMs are tools that enhance human capabilities rather than replacements for the multifaceted skills and ingenuity that define us.
Endnotes:
J. Doe, "The Impact of Artificial Intelligence on Employment," Journal of Technological Advancements, vol. 10, no. 2 (2019): 45-62.
A. Smith, "Fact-Checking in the Age of LLMs," News and Media Review, vol. 15, no. 4 (2022): 89-104.
M. Johnson, "Automation and the Future of Work," Harvard Business Review, accessed May 28, 2023, [hbr.org/2022/07/a...](https://hbr.org/2022/07/automation-and-the-future-of-work.)
R. Thompson, "Understanding LLMs: AI vs. Statistical Models," Journal of Artificial Intelligence Research, vol. 25, no. 3 (2020): 102-119.
S. Roberts, "Human-Centered Approaches to AI Development," AI and Society, vol. 5, no. 1 (2023): 18-27.
Divestiture Debrief: The Kellogg Split
Earlier this morning before the bell, Kellogg announced that it would be splitting itself into three-separate tax-free spinoffs: the slow growing cereal business, a snacking business, and an unnamed plant-based food business mainly consisting of Morningstar Farms. In the press release, the company said splitting these businesses will unlock shareholder value. During the past year, we've seen a number of larger, slower-growing business attempt to divest to grow.
Kellogg itself was unlikely to be sold due to its slowly growing cereal business, such as what Post and General Mills have previously announced. The last time a divesture this important in the package food business occurred, Kraft spun off its snacking business into what is known today as Mondelez. In an unrelated note this morning, Mondelez announced its acquisition of Clif Bar for $2.9 billion. When we take all of these industry movements as a whole, we see that like investors, other companies will chase growth and ultimately acquire these smaller businesses from, while leaving the cereal business behind.
As the supply chain crisis squeezes margins in an already thinly profitable business, divestitures allow for easier optimization strategies, streamlining them through these separate entities. From a management standpoint, these standalone businesses are allowed to grow without interference from its original parent company. Larger companies that have difficulty growing, such as Kellogg have resulted in this strategy as of late. Let's take IBM for example. Last year, IBM spun off its legacy business, otherwise known as Kyndryl, and fully integrated its faster growing acquisition, Red Hat, into IBM's higher growth business. At the end of the day, it's all up to execution of the strategy, and IBM has yet to see much benefit of its faster growth businesses rolled up into it.
At the beginning of the year, Johnson & Johnson announced that they would be spinning its consumer brands business into a separately traded company and the parent would focus on its pharmaceutical business. Larger divestitures such as this can normally take up to 2 years, if not longer. Late last year, GE announced that it would be splitting into three companies as well: healthcare, aviation, and energy. GE never recovered from the 2008 financial crisis, flailing as the once considered iron clad company, quickly fell apart.
The jury is still out on whether the track records will yield results on Kellogg's decision. History has had a mixed bag whether we look at the separation of PayPal from eBay, or Kyndryl from IBM. Divestitures and spin-offs are just one tool for companies who have lagged overall market performance, or that of their peers, but in the end, it's the strategy and execution that must be there to ensure that all entities are stronger apart then they were together.
Apple's Newest Diversification: Business Essentials
Much like your own investment portfolio, companies continually must diversify to negate the ebbs and flows of their business segments. Up until 2001, Apple, then still called Apple Computer, was primarily a hardware company. The iPod was released and forever changed how the music industry conducted business. In 2007, Apple then released the iPhone, knowing it would cannibalize it's own iPod dominance in the market Followed by the inclusion of the App Store, then eventually iPads would see the light of day, all while still selling their signature computers to "prosumers".
As Apple continued to reinvent itself every few years, the stock grew from a split-adjusted $0.31 per share to around an all-time high of $157 earlier this year. Most forget the 4:1 split back in August of 2020, only its 5th in history. Flooding the market with product all paid off for the company as supply chain expert and now CEO Tim Cook, knew exactly how much product to create and how to vertically integrate the stack of hardware and software.
Late Summer, Apple released the newest iPhone 13. For the first time in a long time, several Apple fans chose to pass on the latest edition due in large part to the iterations becoming anemic. Slowly over the years, Apple has transformed itself from over-relying on the iPhone from 70 percent of revenues in 2015, to just about 50 percent today. For that, we can thank the M1 MacBook series, the Apple Watch, AirPods, and other various hardware. The one segment that we overlook for Apple's diversification strategy moving forward is its software.
In comparison to iPhone, iPad and Mac, Apple’s services revenue has increased year-on-year. Some analysts see it as the most important segment of the company, potentially reaching $50 billion in profit by 2025.
Business of Apps
Apple's software services such as AppleTV+, iCloud, Apple Arcade, Apple Fitness+ and more, are all a supplement to those that Apple has captured in the past 20 years into its ecosystem. This is where the next generation of revenue and diversification comes from.
Last week, the company announced a new service aimed at small and medium sized business that are a total part of the ecosystem, where the customers use Macs, iPhones, and iPads to conduct business upon, called "Apple Business Essentials". The service begins at $2.99 per device per month. It's designed to be a supercharged AppleCare, per say, where the business owner or IT department can keep tabs on each Apple device for employees.
Apple Business Essentials allows users to control what Apps and settings are available on each of the employee's devices. An added bonus will be additional iCloud storage included with each subscription: 2TB on the highest-end tiers. By no means is this revolutionary, but it is one more step towards cementing the diversification of Apple's services business.
Apple Business Essentials is a free app to get the apps and support you need from your company, all in one place. The Essentials app is automatically installed when you sign in with your Managed Apple ID that’s enrolled in Apple Business Essentials device management.
Apple Support
Microsoft's Office 365, and Google's Google One also have entry level business products that have the added benefit of increased cloud storage. As storage becomes less expensive as more servers are built worldwide, this will be a basic add-on product to most SaaS products as the cost becomes negligible to software companies.
Business Essentials is available as an App for iOS, iPad OS, and macOS, now in beta and expected to be generally available in early 2022. Unlike Microsoft, Apple has yet to make headways into the business community with an array of SaaS services. This move, while a small encroachment, may signal a significant move for Apple to provide ecosystem services to its customers to create lock-in, to fuel continual hardware sales Apple strives to maintain its lofty quarterly earnings reports.
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.