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Apple missed a cute, fitting opportunity with the iPhone 16e’s name - Related to your, digital, opportunity, name, fitting

Apple missed a cute, fitting opportunity with the iPhone 16e’s name

Apple missed a cute, fitting opportunity with the iPhone 16e’s name

Table of Contents Table of Contents You’re family now Family forever E is good, but C is enhanced.

The names of our smartphones matter. Too clunky and we forget, too wordy and we don’t remember, or too bizarre and we won’t say it. They don’t have to mean anything at all, but they need to fit. The new iPhone 16e’s name fits, far more so than the expected alternatives, and it was one of Apple’s best decisions with the phone. But there’s another name I would have preferred even more.

Since rumors began more than a year ago, it was assumed the iPhone 16e would be called the iPhone SE 4, or the iPhone SE (2025), which mostly followed the trend of previous devices in the range. The original iPhone SE was followed by the iPhone SE (2020), then the iPhone SE (2022), so either name was a logical path for Apple to take.

Except the SE name is, well, a bit silly. It not a Special Edition, as SE is supposed to stand for. It’s an iPhone, and all the SE suffix did was turn Apple’s entry phone into an outlier. It’s entirely separate to the brand’s top phones, and if you decide to buy one, you’re not really joining the club. It’s like making a $1 pledge on a Kickstarter project. Sure, you’ve contributed, but you’re hardly a member of the inner circle and you won’t be getting any of the benefits.

When Tim Cook teased the iPhone 16e’s launch, he used the phrase “meet the newest member of the family,” and with the new name, that’s what we’ve done. The iPhone 16e’s name brings it into the family, where it can sit at the big table with the iPhone 16, iPhone 16 Plus, and the two iPhone 16 Pro models too. Sure, the old SE models were all iPhones, but they didn’t have the right number attached, and it set them apart from the latest versions. When people buy an iPhone, they want the latest, and with the iPhone 16e, that’s what they’re getting.

The iPhone 16e has been embraced by the family, and this could make a difference in the future too, should Apple decide to shift away from the vague multi-year improvement schedule it has maintained with the SE series. It could, realistically, announce a new e-series iPhone every year, and ensure it remains a “current” iPhone by adopting the same number strategy. An iPhone 17e would follow the 16e in 2026, for example.

The SE series did show Apple doesn’t feel the need to upgrade its entry-level phone very often though, but it’s the outlier in the industry. New entry-level phones come from practically every other manufacturer on an annual (and sometimes even sooner) basis, and giving the e-series an annual bump, however small, would keep it fresh and exciting for buyers who don’t want to pay for a number-series phone.

While the iPhone 16e’s name fits in with my personal love of logic and order, the continued existence of the iPhone 15 and iPhone 15 Plus in Apple’s range makes it less neat than it could be, but I can forgive it because the pricing structure makes up for it. The iPhone 16e starts at $599, the iPhone 15 at $699, the iPhone 16 at $799, and the 16 Pro at $999. The iPhone 14 has gone, which will frustrate some due to some less than ideal spec differences, but it couldn’t exist alongside the 16e.

During discussions with colleagues after the iPhone 16e was revealed, I stood more or less alone as someone who liked the new name. Detractors compared it to how Motorola has named some of its lowliest budget phones, and also recalled how Samsung used an e suffix on the budget Galaxy S10e. Others are questioning what the E stands for. Entry-level? Economy? Essential?

It’s an odd one, and ultimately doesn’t need to stand for anything at all, but it’s not a letter tied to Apple’s mobile division. Using S, as it has done in the past for some new models, doesn’t seem right either, as those phones were attached to fairly major annual updates. What’s interesting is the S suffix was easy to tie into new capabilities on the device itself, standing for things like Speed and Siri, and this is where Apple may have missed a trick with the iPhone 16e.

It’s a surprise (and perhaps a missed opportunity for the marketing team) Apple didn’t resurrect the letter C. Calling it the iPhone 16c would have fitted right in as a lower cost, but still premium iPhone, just as the old iPhone 5c did in 2013. Plus, it would have connected (no pun intended) the phone with the introduction of the new C1 modem — which is a bigger deal than Apple made it seem — for some cute, geeky brand synergy.

Names do matter, and I like them to fit. I won’t miss the old SE name, but will remember it fondly for other reasons, and love that with a simple rename the iPhone 16e has become a true member of the family. However, for the ultimate in nerdy satisfaction, I’d have really liked to connect the dots between the new phone and the new C1 modem, if Apple had decided to call it the iPhone 16c instead.

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Your most important customer may be AI

Your most important customer may be AI

For example, Meta’s Llama model may perceive your brand as exciting and reliable, whereas OpenAI’s ChatGPT may view it as exciting but not necessarily reliable. Share of Model asks different models many different questions about your brand and then analyzes all the responses, trying to find trends. “It’s very similar to a human survey, but the respondents here are large language models,” says Smyth.

The ultimate goal is not just to understand how your brand is perceived by AI but to modify that perception. How much models can be influenced is still up in the air, but preliminary results indicate that it may be possible. Since the models now show data, if you ask them to search the web, a brand can see where the AI is picking up data.

“We have a brand called Ballantine’s. It’s the No. 2 Scotch whisky that we sell in the world. So it’s a product for mass audiences,” says Gokcen Karaca, head of digital and design at Pernod Ricard, which owns Ballantine’s and a customer using Share of Model. “However, Llama was identifying it as a premium product.” Ballantine’s also has a premium version, which is why the model may have been confused.

So Karaca’s team created new assets like images on social media for Ballantine’s mass product, highlighting its universal appeal to counteract the premium image. It’s not clear yet if the changes are working, but Karaca states early indications are good. “We made tiny changes, and it is taking time. I can’t give you concrete numbers but the trajectory is positive toward our target,” he says.

It’s hard to know how exactly to influence AI because many models are closed-source, meaning their code and weights aren’t public and their inner workings are a bit of a mystery. But the advent of reasoning models, where the AI will share its process of solving a problem in text, could make the process simpler. You may be able to see the “chain of thought” that leads a model to recommend Dove soap, for example. If, in its reasoning, it details how significant a good scent is to its soap recommendation, then the marketer knows what to focus on.

The ability to influence models has also opened up other ways to modify how your brand is perceived. For example, research out of Carnegie Mellon displays that changing the prompt can significantly modify what product an AI recommends.

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How to have a child in the digital age

How to have a child in the digital age

But how do we retain control over our bodies when corporations and the medical establishment have access to our most personal information? What happens when humans stop relying on their village, or even their family, for advice on having a kid and instead go online, where there’s a constant onslaught of information? How do we make sense of the contradictions of the internet—the tension between what’s inherently artificial and the “natural” methods its denizens are so eager to promote? In her new book, Second Life: Having a Child in the Digital Age (Doubleday, 2025), Hess explores these questions while delving into her firsthand experiences with apps, products, algorithms, online forums, advertisers, and more—each promising an easier, healthier, superior path to parenthood. After welcoming her son, who is now healthy, in 2020 and another in 2022, Hess is the perfect person to ask: Is that really what they’re delivering?

Before my pregnancy, I never felt like advertising technology was particularly smart or specific. So when my Instagram ads immediately clocked my pregnancy, it came as a bit of a surprise, and I realized that I was unaware of exactly how ad tech worked and how vast its reach was. It felt particularly eerie in this case because in the beginning my pregnancy was a secret that I kept from everyone except my spouse, so “the internet” was the only thing that was talking to me about it. Advertising became so personalized that it started to feel intimate, even though it was the opposite of that—it represented the corporate obliteration of my privacy. The pregnancy ads reached me before a doctor would even agree to see me.

Though your book was written before generative AI became so ubiquitous, I imagine you’ve thought about how it changes things. You write, “As soon as I got pregnant, I typed ‘what to do when you get pregnant’ in my phone, and now advertisers were supplying their own answers.” What do the rise of AI and the dramatic changes in search mean for someone who gets pregnant today and goes online for answers?

I just googled “what to do when you get pregnant” to see what Google’s generative AI widget tells me now, and it’s largely spitting out commonsensical recommendations: Make an appointment to see a doctor. Stop smoking cigarettes. That is followed by sponsored content from Babylist, an online baby registry firm that is deeply enmeshed in the ad-tech system, and Perelel, a startup that sells expensive prenatal supplements.

So whether or not the search engine is using AI, the information it’s providing to the newly pregnant is not particularly helpful or meaningful.

The Clue period-tracking app AMIE CHUNG/TRUNK ARCHIVE.

The internet “made me feel like I had some kind of relationship with my phone, when all it was really doing was staging a scene of information that it could monetize.”.

For me, the oddly tantalizing thing was that I had asked the internet a question and it gave me something in response, as if we had a reciprocal relationship. So even before AI was embedded in these systems, they were fulfilling the same role for me—as a kind of synthetic conversation partner. It made me feel like I had some kind of relationship with my phone, when all it was really doing was staging a scene of information that it could monetize.

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Market Impact Analysis

Market Growth Trend

2018201920202021202220232024
12.0%14.4%15.2%16.8%17.8%18.3%18.5%
12.0%14.4%15.2%16.8%17.8%18.3%18.5% 2018201920202021202220232024

Quarterly Growth Rate

Q1 2024 Q2 2024 Q3 2024 Q4 2024
16.8% 17.5% 18.2% 18.5%
16.8% Q1 17.5% Q2 18.2% Q3 18.5% Q4

Market Segments and Growth Drivers

Segment Market Share Growth Rate
Digital Transformation31%22.5%
IoT Solutions24%19.8%
Blockchain13%24.9%
AR/VR Applications18%29.5%
Other Innovations14%15.7%
Digital Transformation31.0%IoT Solutions24.0%Blockchain13.0%AR/VR Applications18.0%Other Innovations14.0%

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity:

Innovation Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity AI/ML Blockchain VR/AR Cloud Mobile

Competitive Landscape Analysis

Company Market Share
Amazon Web Services16.3%
Microsoft Azure14.7%
Google Cloud9.8%
IBM Digital8.5%
Salesforce7.9%

Future Outlook and Predictions

The Apple Missed Cute landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:

Year-by-Year Technology Evolution

Based on current trajectory and expert analyses, we can project the following development timeline:

2024Early adopters begin implementing specialized solutions with measurable results
2025Industry standards emerging to facilitate broader adoption and integration
2026Mainstream adoption begins as technical barriers are addressed
2027Integration with adjacent technologies creates new capabilities
2028Business models transform as capabilities mature
2029Technology becomes embedded in core infrastructure and processes
2030New paradigms emerge as the technology reaches full maturity

Technology Maturity Curve

Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:

Time / Development Stage Adoption / Maturity Innovation Early Adoption Growth Maturity Decline/Legacy Emerging Tech Current Focus Established Tech Mature Solutions (Interactive diagram available in full report)

Innovation Trigger

  • Generative AI for specialized domains
  • Blockchain for supply chain verification

Peak of Inflated Expectations

  • Digital twins for business processes
  • Quantum-resistant cryptography

Trough of Disillusionment

  • Consumer AR/VR applications
  • General-purpose blockchain

Slope of Enlightenment

  • AI-driven analytics
  • Edge computing

Plateau of Productivity

  • Cloud infrastructure
  • Mobile applications

Technology Evolution Timeline

1-2 Years
  • Technology adoption accelerating across industries
  • digital transformation initiatives becoming mainstream
3-5 Years
  • Significant transformation of business processes through advanced technologies
  • new digital business models emerging
5+ Years
  • Fundamental shifts in how technology integrates with business and society
  • emergence of new technology paradigms

Expert Perspectives

Leading experts in the digital innovation sector provide diverse perspectives on how the landscape will evolve over the coming years:

"Technology transformation will continue to accelerate, creating both challenges and opportunities."

— Industry Expert

"Organizations must balance innovation with practical implementation to achieve meaningful results."

— Technology Analyst

"The most successful adopters will focus on business outcomes rather than technology for its own sake."

— Research Director

Areas of Expert Consensus

  • Acceleration of Innovation: The pace of technological evolution will continue to increase
  • Practical Integration: Focus will shift from proof-of-concept to operational deployment
  • Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
  • Regulatory Influence: Regulatory frameworks will increasingly shape technology development

Short-Term Outlook (1-2 Years)

In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing digital innovation challenges:

  • Technology adoption accelerating across industries
  • digital transformation initiatives becoming mainstream

These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.

Mid-Term Outlook (3-5 Years)

As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:

  • Significant transformation of business processes through advanced technologies
  • new digital business models emerging

This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.

Long-Term Outlook (5+ Years)

Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:

  • Fundamental shifts in how technology integrates with business and society
  • emergence of new technology paradigms

These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.

Key Risk Factors and Uncertainties

Several critical factors could significantly impact the trajectory of digital innovation evolution:

Legacy system integration challenges
Change management barriers
ROI uncertainty

Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.

Alternative Future Scenarios

The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:

Optimistic Scenario

Rapid adoption of advanced technologies with significant business impact

Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.

Probability: 25-30%

Base Case Scenario

Measured implementation with incremental improvements

Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.

Probability: 50-60%

Conservative Scenario

Technical and organizational barriers limiting effective adoption

Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.

Probability: 15-20%

Scenario Comparison Matrix

FactorOptimisticBase CaseConservative
Implementation TimelineAcceleratedSteadyDelayed
Market AdoptionWidespreadSelectiveLimited
Technology EvolutionRapidProgressiveIncremental
Regulatory EnvironmentSupportiveBalancedRestrictive
Business ImpactTransformativeSignificantModest

Transformational Impact

Technology becoming increasingly embedded in all aspects of business operations. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.

The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.

Implementation Challenges

Technical complexity and organizational readiness remain key challenges. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.

Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.

Key Innovations to Watch

Artificial intelligence, distributed systems, and automation technologies leading innovation. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.

Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.

Technical Glossary

Key technical terms and definitions to help understand the technologies discussed in this article.

Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.

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algorithm intermediate

algorithm

platform intermediate

interface Platforms provide standardized environments that reduce development complexity and enable ecosystem growth through shared functionality and integration capabilities.