Electronics Guide

Ambitious Vision and Technical Limitations

The Newton embodied an ambitious vision of personal digital assistance. CEO John Sculley championed the concept of a "Personal Digital Assistant" that would manage calendars, contacts, notes, and communications in a pocket-sized device. The Newton would recognize handwritten input, learn from user behavior, and connect wirelessly to networks and other devices. This vision anticipated smartphone capabilities by more than a decade.

However, the technology available in 1993 could not fully deliver on this vision. The Newton's handwriting recognition, while innovative, proved frustratingly inaccurate, becoming an object of widespread mockery including satire on television shows. The device's ARM processor, though efficient for its time, struggled with the computational demands of recognition algorithms. Battery technology limited operational time. The display, while pioneering, offered limited resolution and no backlighting for low-light conditions.

Physical size also presented challenges. The Newton was too large for a pocket yet too limited to replace a laptop, creating an awkward middle ground that failed to establish a clear use case. Users who might have tolerated limitations for a truly pocket-sized device found those same limitations unacceptable in something requiring a bag to transport.

Infrastructure and Ecosystem Gaps

Beyond device limitations, the Newton entered a world lacking the infrastructure that later made tablets transformative. Wireless connectivity remained expensive, slow, and geographically limited. The internet existed but had not yet achieved mass adoption; the World Wide Web was barely a year old as a public phenomenon. Without ubiquitous connectivity, a connected personal assistant could only offer a fraction of its potential value.

The software ecosystem also remained undeveloped. While Apple cultivated third-party Newton developers, the relatively small installed base limited developer interest, which in turn limited device appeal in a classic chicken-and-egg problem. Users found few applications beyond Apple's bundled software, reducing the device's practical utility.

When Apple discontinued Newton in 1998, the product was widely viewed as a failure. Yet many Newton innovations reappeared in later successful products. The iPhone's touchscreen interface, the iPad's tablet form factor, and numerous software concepts all traced conceptual lineage to Newton experiments. The failure taught Apple lessons about technology readiness, market timing, and the importance of ecosystem development that informed later successes.

Lessons for Technology Timing

The Newton's failure illustrated several principles about technology timing. First, component technology must be sufficiently mature to deliver on product promises; the Newton's handwriting recognition worked well enough to demonstrate the concept but not well enough for practical daily use. Second, supporting infrastructure including connectivity and content ecosystems must exist or be developable on reasonable timelines. Third, product positioning must address genuine user needs that cannot be better met by existing solutions; the Newton competed with paper organizers that, while less sophisticated, were lighter, cheaper, and entirely reliable.

Other companies attempted similar devices during this period with similar results. Palm would later find success with the Palm Pilot by dramatically simplifying the concept, accepting input via a stylized alphabet rather than attempting natural handwriting recognition, and focusing narrowly on personal information management rather than attempting to be a general computing platform.

The Promise of Immersive Computing

Virtual reality's appeal was powerful and genuine. The idea of stepping into digital worlds, experiencing environments impossible in physical reality, and interacting with information spatially rather than through flat screens captured imaginations across technology, entertainment, and business sectors. Films like "The Lawnmower Man" (1992) and later "The Matrix" (1999) explored VR concepts that seemed tantalizingly close to reality.

Companies including VPL Research, founded by VR pioneer Jaron Lanier, developed sophisticated systems incorporating head-mounted displays, data gloves, and position tracking. These systems demonstrated that immersive virtual environments were technically achievable, generating excitement about impending transformation of human-computer interaction.

Technical and Economic Barriers

The 1990s VR systems faced severe practical limitations. Head-mounted displays offered low resolution, limited field of view, and insufficient refresh rates, creating visual experiences that fell far short of expectations shaped by science fiction. Many users experienced motion sickness from latency between head movement and display updates. Tracking systems were expensive, required dedicated spaces, and remained imprecise by later standards.

Computing power represented perhaps the most fundamental constraint. Rendering convincing 3D environments in real-time at the frame rates needed to prevent disorientation required computational capabilities far exceeding what was affordable for consumer applications. Professional systems cost tens of thousands of dollars and still delivered experiences that, while impressive for their time, could not sustain extended engagement.

Arcade-style VR installations like those from Virtuality attempted to make VR accessible by amortizing equipment costs across many users. These attracted novelty-seekers but could not overcome technical limitations sufficiently to build sustainable businesses. After initial curiosity wore off, customers rarely returned for experiences that were novel but ultimately unsatisfying.

Consumer VR Attempts

Several companies attempted consumer VR products during this period. Nintendo's Virtual Boy, released in 1995, represented the most prominent effort. Priced at $180, the Virtual Boy offered stereoscopic 3D gaming through a tabletop head-mounted display. However, the system displayed only red and black graphics, caused eye strain during extended use, and offered a limited game library. Nintendo discontinued it within a year, having sold only about 770,000 units.

Other consumer VR products similarly failed to find markets. The gap between consumer expectations, shaped by science fiction and marketing materials, and actual delivered experiences proved too large. Users who had imagined Star Trek holodecks found themselves in crude, often uncomfortable environments that bore little resemblance to promised immersion.

The Long Path to VR Revival

Virtual reality would spend nearly two decades in relative dormancy before conditions enabled a genuine revival. When Palmer Luckey launched the Oculus Rift Kickstarter in 2012, smartphone component supply chains had matured to provide affordable high-resolution displays, motion sensors, and processors. Facebook's acquisition of Oculus for $2 billion in 2014 signaled renewed confidence in VR's potential.

Even the VR revival that followed has proceeded more slowly than enthusiasts anticipated. By the mid-2020s, VR headsets had become capable, affordable devices, yet mainstream adoption remained limited. The 1990s lesson that compelling content and clear use cases matter as much as technical capability continued to apply, as the industry worked to define VR's role beyond gaming and specialized applications.

IBM Simon: The First Smartphone

The IBM Simon Personal Communicator, released in 1994, is generally recognized as the first smartphone. Combining cellular phone capabilities with touchscreen computing, the Simon offered a calendar, address book, calculator, notepad, email, and even third-party applications. At $899 with a two-year cellular contract, it targeted business users seeking mobile productivity.

The Simon demonstrated that smartphone concepts were technologically feasible but also revealed practical barriers to adoption. The device weighed over a pound, offered only one hour of battery life, and lacked wireless data connectivity beyond cellular voice. Its touchscreen required a stylus for accurate input. Sales reached only about 50,000 units before IBM discontinued the product after six months.

Palm and Windows CE Smartphones

The late 1990s and early 2000s saw more sophisticated smartphone attempts. Palm's acquisition of Handspring brought the Treo line, which combined Palm's successful PDA platform with cellular phone capabilities. Microsoft's Windows CE and later Windows Mobile platforms powered smartphones from various manufacturers. BlackBerry carved out a successful niche focused on enterprise email.

These products achieved meaningful market success among business users but failed to achieve mass consumer adoption. User interfaces designed for stylus input proved awkward for casual use. Tiny physical keyboards, while enabling text input, cramped into small form factors. Applications remained limited, and browsing the internet on small screens with slow data connections proved frustrating.

Why Early Smartphones Failed to Transform

Early smartphones faced a constellation of limiting factors. Cellular data networks remained too slow for rich media experiences. Touchscreens capable of capacitive multi-touch input had not yet become cost-effective for consumer devices. Processors powerful enough to render sophisticated interfaces while maintaining battery life did not exist. App development remained fragmented across incompatible platforms with limited distribution mechanisms.

Perhaps most importantly, early smartphone makers conceived their devices as mobile computers rather than reimagining the mobile experience from first principles. They attempted to shrink desktop computing paradigms onto small screens rather than designing interfaces optimized for touch interaction and mobile contexts. This approach produced devices that felt like compromised computers rather than purpose-built mobile tools.

iPhone's Timing Advantages

When Apple introduced the iPhone in 2007, multiple enabling factors had converged. Capacitive touchscreens enabled finger-based input without styluses. ARM processors had reached sufficient power and efficiency for sophisticated mobile computing. Flash storage provided fast, reliable solid-state storage. 3G networks, while not yet ubiquitous, offered data speeds adequate for mobile web browsing and application downloads.

Apple also benefited from studying earlier attempts. The company understood that a software keyboard could provide a larger screen than physical keyboards while adapting to different input modes. It recognized that a curated application marketplace could solve software quality and discovery problems that plagued earlier platforms. Perhaps most crucially, Apple designed a user interface optimized for touch from the beginning rather than adapting desktop concepts.

The iPhone's success was not predetermined; its initial lack of an app store, 3G connectivity, and enterprise features drew criticism. But Apple had timed its entry to a moment when enabling technologies had matured while designing an experience that transcended predecessors' limitations.

The Interactive TV Vision

Interactive television promised to merge the reach and impact of broadcast television with computing's interactivity and personalization. Viewers would order products from advertisements, vote in polls, access supplementary information about programs, play along with game shows, and eventually choose their own camera angles or narrative paths. Television would evolve from one-way broadcasting to two-way communication.

The vision aligned with broader convergence expectations that computing, telecommunications, and media would merge into unified digital platforms. Companies throughout these industries invested heavily in interactive TV trials and product development, convinced that whoever mastered this convergence would dominate the future of entertainment and commerce.

Major Interactive TV Initiatives

Time Warner's Full Service Network, launched in Orlando, Florida in 1994, represented one of the most ambitious interactive TV trials. The system offered video on demand, interactive shopping, games, and email through set-top boxes connected via fiber optic networks. Despite spending approximately $100 million, Time Warner shut down the trial in 1997, having demonstrated that while the technology could work, consumers showed limited enthusiasm for interactive features.

Microsoft invested heavily in interactive TV through various initiatives including WebTV (acquired for $425 million in 1997) and later through the Mediaroom IPTV platform. While these efforts survived longer than many competitors, they never achieved the transformative impact Microsoft envisioned. Set-top boxes proved expensive, user interfaces clunky, and consumer interest tepid.

Telecommunications companies including Bell Atlantic, US West, and others conducted trials that similarly demonstrated technical feasibility without commercial viability. Each trial revealed the same pattern: while interactive capabilities worked technically, they failed to offer sufficient value beyond traditional television to justify the cost and complexity of deployment.

Why Interactive TV Failed

Interactive television failed for multiple interconnected reasons. Infrastructure costs proved prohibitive; delivering interactive services required substantial investments in network capacity, set-top boxes, and back-end systems that could not be recovered through available revenue streams. Content creation for interactive formats required new skills and investment that media companies hesitated to make for uncertain returns.

Consumer behavior presented perhaps the greatest challenge. Television viewing often occurred in passive, relaxed states where viewers wanted entertainment delivered to them rather than requiring active engagement. The "lean back" experience that television provided differed fundamentally from the "lean forward" engagement that interactivity demanded. Viewers who wanted interaction increasingly turned to personal computers, which offered richer experiences with fewer constraints.

The internet's emergence provided alternative paths to interactive content that rendered dedicated interactive TV systems unnecessary. By the time broadband internet became widely available, viewers could access interactive content on computers and later on mobile devices, without requiring specialized television infrastructure.

Interactive Television's Eventual Arrival

Many capabilities envisioned for 1990s interactive TV eventually arrived through different paths. Netflix and streaming services delivered on-demand video without specialized infrastructure beyond broadband internet. Social media enabled real-time engagement around television programming. Smart TVs integrated internet connectivity directly into displays. Yet these developments occurred through evolution of internet and computing technologies rather than through transformation of broadcast television.

The interactive TV failure demonstrated that technology alone cannot create markets. Even when systems work technically and concepts seem obviously valuable, actual consumer adoption depends on integration into existing behaviors, reasonable costs, and genuine utility that justifies change. Billions of dollars invested in interactive TV yielded little direct return, though lessons learned informed later successful digital media developments.

Early Home Automation Attempts

The X10 protocol, developed in 1975, enabled home automation through power line communication, allowing devices to send simple commands through existing electrical wiring. X10 and compatible systems found niche markets among enthusiasts and accessibility applications but never achieved mass adoption. Installation remained complex, reliability proved inconsistent, and available devices offered limited functionality.

The 1990s and 2000s saw various attempts to create more sophisticated home automation systems. Companies including Honeywell, Control4, Crestron, and others offered systems that could integrate lighting, climate, entertainment, and security into unified control. However, these systems typically required professional installation costing thousands of dollars and appealed primarily to luxury home markets.

Fragmentation and Interoperability Challenges

Home automation suffered from severe fragmentation. Multiple incompatible protocols including X10, Insteon, Z-Wave, ZigBee, and various proprietary systems divided the market. Devices from different manufacturers often could not communicate, forcing consumers to choose ecosystems with limited product selection or accept systems that could not be unified.

Installation complexity deterred adoption. Running dedicated control wiring, programming sophisticated systems, and integrating devices from multiple manufacturers required skills beyond most homeowners' capabilities. Professional installation addressed these challenges but added costs that could exceed the devices themselves.

Reliability and maintenance presented ongoing concerns. Home automation systems that worked initially often failed as components aged, software required updates, or home modifications affected wiring. Unlike traditional switches and thermostats that functioned for decades without attention, automated systems required ongoing maintenance that many homeowners found burdensome.

The Connected Home Finally Arrives

Several developments eventually enabled more successful home automation. WiFi became ubiquitous, providing wireless connectivity that eliminated wiring complexity. Smartphones provided natural interfaces for home control, replacing expensive dedicated controllers. Cloud services enabled sophisticated functionality without requiring local computing infrastructure. Voice assistants from Amazon, Google, and Apple provided intuitive interaction methods.

Products like the Nest thermostat, Philips Hue lighting, and Ring doorbells demonstrated that home automation could succeed when individual products offered clear value without requiring whole-home systems. Consumers could adopt gradually, adding devices as interests and budgets allowed rather than committing to comprehensive systems upfront.

Even with these advances, home automation adoption has proceeded more slowly than enthusiasts anticipated. Many consumers find current solutions insufficiently compelling to justify cost and complexity. Interoperability remains imperfect, and security concerns have emerged as connected devices create new vulnerabilities. The smart home remains a work in progress decades after initial visions.

The First AI Winter (1974-1980)

Early AI research in the 1950s and 1960s generated bold predictions about machine intelligence. Pioneers including Herbert Simon, who predicted that machines would be capable of any human intellectual task within twenty years, and Marvin Minsky, who declared that the problem of creating artificial intelligence would be "substantially solved" within a generation, established expectations that could not be met by available computing power and algorithms.

By the mid-1970s, the gap between predictions and accomplishments had become undeniable. The Lighthill Report in the United Kingdom criticized AI research as failing to achieve its objectives, leading to dramatic funding cuts. American funding agencies similarly reduced support. Research continued but at reduced intensity, as many researchers redirected toward other fields.

The first AI winter demonstrated how premature claims can damage entire research fields. Overpromising by prominent researchers created expectations that realistic progress could not satisfy, leading to disillusionment that affected even responsible researchers working on achievable objectives.

Expert Systems Boom and Bust

AI enthusiasm revived in the 1980s around expert systems, programs that encoded human expertise in rule-based formats to make decisions in specialized domains. Companies invested heavily in AI, often purchasing dedicated Lisp machines optimized for AI workloads. Japan's Fifth Generation Computer Project, aiming to create intelligent computers, generated international responses including similar initiatives in Europe and America.

Expert systems achieved genuine success in narrow applications including medical diagnosis, financial analysis, and manufacturing optimization. However, they proved brittle when confronting situations outside their encoded knowledge, difficult to maintain as domains evolved, and limited to well-defined problems where expert knowledge could be explicitly articulated.

The expert systems boom ended in the late 1980s as limitations became apparent and specialized AI hardware proved unnecessary as general-purpose computers improved. The second AI winter that followed lasted roughly from 1987 through the 1990s, again reducing funding and causing many AI researchers to reframe their work using alternative terminology.

The Current AI Spring

The current AI revival, driven primarily by deep learning and enabled by massive computing power and data availability, has achieved capabilities that previous approaches could not match. Image recognition, natural language processing, and other applications have reached or exceeded human performance on specific tasks. Unlike previous AI booms, current systems demonstrate genuine utility in commercial applications.

However, the history of AI winters offers cautionary lessons. Current AI enthusiasm may once again be generating expectations that technology cannot satisfy. Claims about approaching artificial general intelligence echo earlier predictions that proved premature. The pattern of boom-and-bust cycles suggests that managing expectations remains crucial for sustained AI development.

Understanding AI winters helps contextualize current developments. Many fundamental insights underlying modern AI were developed during earlier periods but awaited sufficient computing power and data to become practical. The researchers who maintained work through winter periods ultimately enabled current capabilities, even if their contributions were undervalued during lean years.

GO Corporation and PenPoint

GO Corporation, founded in 1987, represented the most ambitious early pen computing effort. The company developed PenPoint, an operating system designed from scratch for pen-based tablet computers. PenPoint featured gesture-based interaction, handwriting recognition, and a notebook metaphor organizing documents into tabs. Major corporations including IBM and AT&T invested in GO, recognizing pen computing's potential for mobile professionals.

Despite sophisticated technology and significant investment, GO struggled commercially. The tablet hardware running PenPoint remained expensive and bulky. Handwriting recognition, while functional, required training and remained error-prone. Applications developed specifically for PenPoint were limited, and porting traditional software proved difficult.

GO ultimately failed, selling its intellectual property to AT&T and ceasing operations in 1994. The company's story, documented in Jerry Kaplan's book "Startup," became a cautionary tale about the challenges facing pioneering technology companies that must create markets while simultaneously developing products.

Microsoft Tablet PC

Microsoft launched the Tablet PC initiative in 2002, promoting portable computers with pen input and handwriting recognition running Windows XP Tablet PC Edition. Bill Gates personally championed the initiative, predicting Tablet PCs would become the most popular form of computer within five years.

Tablet PCs achieved modest success in specific markets including healthcare and field service, where pen input offered advantages over keyboards. However, mass consumer adoption never materialized. The devices proved expensive, heavy, and offered limited advantages over conventional laptops for most users. Windows, designed for keyboard and mouse input, never felt natural with a pen.

When Apple introduced the iPad in 2010 with finger-based touch input rather than pen input, the contrast proved instructive. Apple had explicitly rejected styluses, with Steve Jobs memorably asking "Who wants a stylus?" at the iPhone launch. While Microsoft had invested in sophisticated handwriting recognition, Apple bet that direct finger manipulation would prove more intuitive for most users.

Pen Computing's Eventual Niche

Pen input has found successful niches rather than achieving the universal adoption early advocates predicted. The Apple Pencil, Samsung S Pen, and Microsoft Surface Pen offer precise input for artists, designers, and note-takers. Professional applications including medical records, package delivery confirmation, and field inspections benefit from handwritten input.

The pen computing story demonstrates how technologies can be right about some use cases while wrong about universal applicability. Pen input genuinely offers advantages for precision work and handwriting capture, but most computing tasks are better served by finger touch, keyboards, or voice input. Premature technologies sometimes fail not by being wrong but by overreaching beyond their appropriate applications.

Research Pioneers

MIT's Media Laboratory became a center for wearable computing research, with Steve Mann developing increasingly sophisticated wearable systems beginning in the 1980s. Mann's devices, which he wore continuously for decades, demonstrated possibilities including augmented reality overlays, lifelogging, and continuous computing access. His work influenced generations of wearable computing researchers and anticipated concepts that later became commercial products.

Thad Starner, another MIT researcher who began wearing computers in the early 1990s, later became a technical lead on Google Glass. Starner's research explored how wearable computing could augment human memory and provide contextual information access. These research efforts proved technically feasible but highlighted challenges in power consumption, display technology, and social acceptance that would constrain commercial efforts.

Commercial Wearable Attempts

Various companies attempted commercial wearable computing products with limited success. Xybernaut produced wearable computers for industrial applications beginning in the 1990s, targeting maintenance, warehousing, and field service workers who needed computing access while keeping hands free. While finding niche markets, Xybernaut never achieved the mainstream success its ambitions suggested and eventually filed for bankruptcy.

Consumer wearables fared even less well. Devices like the Timex Datalink, which could receive data downloads from computer screens, offered glimpses of connected wearables but provided limited functionality. Early Bluetooth headsets, fitness trackers, and smart jewelry attempted to bring computing to the body with mixed results.

Google Glass and Public Resistance

Google Glass, released to developers in 2013 and briefly available to consumers, became the most prominent wearable computing product of its era and also one of the most controversial. Glass featured a small display visible in the wearer's peripheral vision, a camera, and voice-controlled computing capabilities. Google positioned Glass as the future of personal computing.

Glass encountered fierce social resistance. The integrated camera raised privacy concerns, as observers could not tell when Glass wearers were recording. The distinctive appearance identified wearers as "Glassholes" to critics who viewed the devices as intrusive and anti-social. Some establishments banned Glass wearers, and the products became symbols of technology overreach.

Google discontinued consumer Glass in 2015, though enterprise versions continued for industrial applications. The Glass experience demonstrated that wearable computing faces social and cultural challenges beyond technical ones. Technologies worn visibly on the face affect social interactions in ways that pocket devices do not, requiring careful attention to social acceptance.

Wearables That Succeeded

The Apple Watch, launched in 2015, achieved the mainstream success that earlier wearables had not. Several factors contributed to this success. The Watch built on familiar watch form factors rather than requiring users to adopt new product categories. It emphasized health and fitness features that provided clear value. Integration with the iPhone ecosystem reduced complexity. Perhaps most importantly, the Watch could be worn without constantly signaling "technology user" to observers.

The contrast between Google Glass and Apple Watch illustrates how form factor and social positioning influence wearable adoption. Both devices offered similar core capabilities including notifications, voice input, and sensor data. But the Watch's familiar form and emphasis on personal utility rather than recording or augmented reality enabled acceptance that Glass's conspicuous design prevented.

Ecosystem Readiness

Successful technologies rarely succeed in isolation. They require supporting ecosystems including complementary products, infrastructure, skills, and content. The Newton needed wireless networks and app developers. Virtual reality needed powerful, affordable processors and compelling content. Interactive TV needed broadband infrastructure and content designed for interactivity.

Pioneering technologies often must build their own ecosystems, a task that may exceed any single company's capabilities. Even well-funded efforts can fail when ecosystem development proceeds too slowly or requires coordination among companies with misaligned incentives. Technologies that can leverage existing ecosystems or that catalyze ecosystem development enjoy significant advantages.

Component Technology Maturity

Complex products depend on multiple component technologies that must each reach sufficient maturity. Smartphones required mature touchscreens, processors, batteries, wireless radios, and flash storage. VR headsets needed high-resolution displays, precise motion tracking, and powerful graphics processing. When any critical component remains immature, the resulting product falls short of requirements for success.

Component technology improvement often follows predictable trajectories, enabling forecasts of when products might become viable. Moore's Law predicted processor improvement; similar patterns governed display resolution, battery energy density, and sensor capabilities. Products launched before component technologies reached critical thresholds often failed, while those that waited for or anticipated maturation could succeed.

Cost Reduction Timing

Many technologies are technically feasible long before they become economically viable. Manufacturing costs must decline to levels that target markets can afford. This reduction typically requires production scale, manufacturing learning, and sometimes entirely new production processes. Technologies launched before adequate cost reduction can succeed in luxury or professional markets while failing to achieve mass adoption.

Timing market entry to coincide with crossing cost thresholds offers advantages. Companies that enter too early bear development costs without achieving scale. Those that enter too late find markets occupied by earlier entrants. Estimating when costs will reach viable levels, and positioning accordingly, represents a critical strategic skill.

Cultural and Behavioral Readiness

Technologies must also align with cultural expectations and behavioral patterns. Google Glass faced social resistance that no amount of technical improvement could overcome. Home automation struggled against established behaviors around home control. Interactive TV demanded engagement modes that television viewers did not want.

Cultural readiness can be harder to assess than technical or economic factors. Behaviors that seem likely to change may prove stubbornly persistent, while unexpected shifts can suddenly make technologies viable. The smartphone's success depended partly on cultural acceptance of constant connectivity and public device use that might not have been predictable.

Distinguishing Vision from Timing

Many failed technologies embodied correct visions that were simply premature. The Newton's vision of personal digital assistance was sound; only its timing was wrong. Similarly, 1990s VR enthusiasts correctly anticipated immersive computing's potential, even if their timing proved decades premature. Distinguishing between flawed concepts and premature timing helps avoid prematurely abandoning valuable ideas.

When technologies fail, careful analysis can reveal whether failure resulted from fundamentally mistaken concepts or merely from timing. Concepts that fail repeatedly despite various implementations may be genuinely flawed. Those that fail due to identifiable limiting factors that are improving may be worth revisiting as conditions change.

Watching Enabling Technologies

Successful timing often requires monitoring enabling technologies for signs of approaching maturity. Smartphone success became more predictable as touchscreens, processors, and mobile networks approached critical thresholds. VR revival became plausible as smartphone supply chains delivered affordable, high-quality displays and motion sensors. Watching enabling technology trajectories can reveal windows for successful product introduction.

Learning from Pioneers' Mistakes

Companies that succeed with technologies that earlier attempts failed to commercialize often benefit from studying predecessors' experiences. Apple's iPhone team certainly understood why earlier smartphones had limited appeal. Oculus studied 1990s VR failures when designing its headsets. Learning from pioneers' mistakes, without bearing their development costs, provides significant advantages to well-timed followers.

Managing Expectations

Premature technologies often fail partly because expectations exceed what current implementations can deliver. The gap between anticipated and actual experiences causes disappointment that can poison markets for years. Managing expectations, delivering experiences that match or exceed what is promised, helps technologies succeed even when limitations exist.