How many iDownloaders does it take to screw an App Store?

Search results for “iDownloader” at Apple App Store:

IDownloaders

Yes, it’s a big operation. Yes, there’ll be a million apps soon. Yes, many apps will inevitably be similar. Yes, shady developers steal other developers’ IP. Yes, all sorts of people try to game it. Yes, the power law may apply to revenues. Yes, you can’t please everyone all the time. Yes, other app stores may be worse. Yes, the App Store was once the crown jewel of Apple’s mobile empire.

Yes, there are many ways to spin this… None fits the bill as much as the notion that Apple’s inability or unwillingness to fundamentally improve categorization, discovery, navigation, display, promotion, fraud, pricing and reviews at the App Store has been most glaring.

Chomp change, indeed.

Can Siri go deaf, mute and blind?

Earlier in “Is Siri really Apple’s future?” I outlined Siri’s strategic promise as a transition from procedural search to task completion and transactions. This time, I’ll explore that future in the context of two emerging trends:

  • Internet of Things is about objects as simple as RFID chips slapped on shipping containers and as vital as artificial organs sending and receiving signals to operate properly inside our bodies. It’s about the connectivity of computing objects without direct human intervention.
  • The best interface is no interface is about objects and tools that we interact with that no longer require elaborate or even minimal user interfaces to get things done. Like self-opening doors, it’s about giving form to objects so that their user interface is hidden in their user experience.

Apple’s strength has always been the hardware and software it creates that we love to carry, touch, interact with and talk about lovingly — above their mere utility — like jewelry, as Jony Ive calls it. So, at first, it seems these two trends — objects talking to each other and objects without discernible UIs — constitute a potential danger for Apple, which thrives on design of human touch and attention. What happens to Apple’s design advantage in an age of objects performing simple discreet tasks or “intuiting” and brokering our next command among themselves without the need for our touch or gaze? Indeed, what happens to UI design, in general, in an ocean of “interface-less” objects inter-networked ubiquitously?

Looks good, sounds better

Fortunately, though a star in her own right, Siri isn’t wedded to the screen. Even though she speaks in many tongues, Siri doesn’t need to speak (or listen, for that matter) to go about her business, either. Yes, Siri uses interface props like fancy cards, torn printouts, maps and a personable voice, but what makes Siri different is neither visuals nor voice.

Despite the knee-jerk reaction to Siri as “voice recognition for search,” Siri isn’t really about voice. In fact, I’d venture to guess Siri initially didn’t even have a voice. Siri’s more significant promise is about correlation, decisioning, task completion and transaction. The fact that Siri has a sassy “voice” (unlike her competitors) is just endearing “attitude”.

Siri2

Those who are enthusiastic about Siri see her eventually infiltrating many gadgets around us. Often seen liaising with celebrities on TV, Siri is thought to be a shoo-in for the Apple TV interface Oscars, maybe even licensed to other TV manufacturers, for example. And yet the question remains, is Siri too high maintenance? When the most expensive BOM item in an iPhone 5 is the touchscreen at $44, nearly 1/4 costlier than the next item, can Siri afford to live outside of an iPhone without her audio-visual appeal?

Well, she already has. Siri Eyes Free integration is coming to nine automakers early this year, allowing drivers to interact with Siri without having to use the connected iPhone screen.

Sirieyesfree

Given Siri Eyes Free, it’s not that difficult to imagine Siri Touch Free (see and talk but not touch), Siri Talk Free (see and touch but not talk) and so on. People who are impatient with Apple’s often lethargic roll out plans have already imagined Siri in all sorts of places, from aircraft cockpits to smart wristwatches to its rightful place next to an Apple TV.

Over the last decade, enterprise has spent billions to get their “business intelligence” infrastructure to answer analysts’ questions against massive databases from months to weeks to days to hours and even minutes. Now imagine an analyst querying that data by having a “natural” conversation with Siri, orchestrating some future Hadoop setup, continuously relaying nested, iterative questions funneled towards an answer, in real time. Imagine a doctor or a lawyer querying case histories by “conversing” with Siri. Forget voice, imagine Siri’s semantic layer responding to 3D gestures or touches on glass or any sensitized surface. Set aside active participation of a “user” and imagine a monitor with Siri reading microexpressions of a sleeping or crying baby and automatically vocalizing appropriate responses or simply rocking the cradle faster.

Scenarios abound, but can Siri really afford to go fully “embedded”?

There is some precedence. Apple has already created relatively successful devices by eliminating major UI affordances, perhaps best exemplified by the iPod nano ($149) that can become an iPod shuffle ($49) by losing its multitouch screen, made possible by the software magic of Genius, multi-lingual VoiceOver, shuffle, etc. In fact, the iPod shuffle wouldn’t need any buttons whatsoever, save for on/off, if Siri were embedded in it. Any audio functionality it currently has, and much more, could be controlled bi-directionally with ease, in all instances where Siri were functional and socially acceptable. 3G radio plus embedded Siri could also turn that tiny gadget into so many people’s dream of a sub-$100 iPhone.

Ipods2

Grounding Siri

Unfortunately, embedding Siri in devices that look like they may be great targets for Siri functionality isn’t without issues:

  • Offline — Although Siri requires a certain minimum horsepower to do its magic, much of that is spent ingesting and prepping audio to be transmitted to Apple’s servers which do the heavy lifting. Bringing that processing down to an embedded device that doesn’t require a constant connection to Apple maybe computationally feasible. However, Apple’s ability to advance Siri’s voice input decoding accuracy and pattern recognition depend on constant sampling of and adjusting input from tens of millions of Siri users. This would rule out Siri embedded into offline devices and create significant storage and syncing problems with seldom-connected devices.
  • Sensors — One of the key reasons why Siri is such a good fit for smartphones is the number of on-device sensors and the virtually unlimited range of apps it’s surrounded with. Siri is capable of “knowing” not only that you’re walking, but that you’ve also been walking wobbly, for 35 minutes, late at night, in a dark alley, around a dangerous part of a city, alone… and send a pre-designated alert silently on your behalf. While we haven’t seen examples of such deep integration from Apple yet, Siri embedded into devices that lack multiple sensors and apps would severely limit its potential utility.
  • Data — Siri’s utility is directly indexed to her access to data sources and, at this stage, third parties’ search (Yelp), computation (WolframAlpha) and transaction (OpenTable) facilities. Apple does and is expected to continue to add such partners in different domains on a regular basis. Siri embedded in radio-lacking devices that don’t have access to such data and processing, therefore, may be too crippled to be of interest.
  • Fragmentation — People expect to see Siri pop up in all sorts of places and Apple has taken the first step with Siri Eyes Free where Siri gives up her screen to capture the automotive industry. If Siri can drive in a car, does that also mean she can fly on an airplane, sail on a boat or ride on a train? Can she control a TV? Fit inside a wristwatch? Or a refrigerator? While Siri — being software — can technically inhabit anything with a CPU in it, the radio in a device is far more important to Siri than its CPU, for without connecting to Apple (and third party) servers, her utility is severely diminished.
  • Branding — Siri Eyes Free won’t light up the iPhone screen or respond to commands that would require displaying a webpage as an answer. What look like reasonable restrictions on Siri’s capabilities in this context shouldn’t, however, necessarily signal that Apple would create “subsets” of Siri for different domains. More people will use and become accustomed to Siri’s capabilities in iPhones than any other context. Degrading that familiarity significantly just to capture smaller markets wouldn’t be in Apple’s playbook. Instead of trying to embed Siri in everything in sight and thus diluting its brand equity, Apple would likely pair Siri with potential NFC or Bluetooth interfaces to devices in proximity.

What’s Act II for Siri?

In Siri’s debut, Apple has harvested the lowest hanging fruit and teamed up with just a handful of already available data services like Yelp and WolframAlpha, but has not really taken full advantage of on-device data, sensor input or other novel information.

As seen from outside, Siri’s progress at Apple has been slow, especially compared to Google that has had to play catch up. But Google must recognize a strategically indispensable weapon in Google Now (a Siri-for-Android, for all practical purposes) as a hook to those Android device manufacturers that would prefer to bypass Google’s ecosystem. None of them can do anything like it for some time to come, Samsung’s subpar attempts aside.

If you thought Maps was hard, injecting relationship metadata into Siri — fact by fact, domain by domain — is likely an order of magnitude more laborious, so Apple’s got her work cut out for Siri. It’d be prudent not to expect Apple to rush into embedding Siri in its non-signature devices just yet.

“The Creepy Line”

When asked in 2010 about the possibility of a Google “implant,” Google’s then-CEO Eric Schmidt famously said:

“Google policy is to get right up to the creepy line and not cross it.

With your permission you give us more information about you, about your friends, and we can improve the quality of our searches. We don’t need you to type at all. We know where you are. We know where you’ve been. We can more or less know what you’re thinking about.”

Since that reassuring depiction of what awaits us in the future, Google has danced energetically around “the creepy line” many times, from subverting users’ privacy preferences in Safari and paying the largest FTC fine in history to introducing the omniscient Google Glass that gets as close to human trafficking as possible without drilling into the brain.

When the internet behemoth raises the bar, others rush to conquer and some manage to surpass it. Buried in the minutiae of CES 2013, in a booth not much smaller than a 10,000-inch Samsung UHD TV, was Affectiva, showcasing its primary product Affdex:

“Affdex tracks facial and head gestures in real-time using key points on viewers’ face to recognize a rich array of emotional and cognitive states, such as enjoyment, attention and confusion.”

affdex1

Affdex2

Deciphering concealed emotions by “reading” facial microexpressions, popularized by Paul Ekman and the hit TV series Lie To Me, is nothing new, of course. What’s lifting us over the creepy line is the imminent ubiquity of this technology, all packaged into a web browser and a notebook with a webcam, no installation required.

Affdex3

Eyes Wide Shut

Today, Affectiva asks viewers’ permission to record, as they watch TV commercials. What happens tomorrow? After all, DNA evidence in courts was first used in the late 1980s and has been controversial ever since. It’s been used to exonerate incarcerated people as well as abused and misused to convict innocent ones. Like DNA analysis, facial expression reading technology will advance and may attain similar stature in law and in other fields…Some day.

Currently, however, along with its twin brother face recognition technology, microexpression reading isn’t yet firmly grounded in law. This uncertainty gives it the necessary space to evolve technologically but also also opens the door to significant privacy and security abuse.

Janus-faced

The technology, when packaged into a smartphone, for example, can be used to help some of those with Asperger’s syndrome to read facial expressions. But it can also be used in a videotelephony app as a surreptitious “lie detector.” It could be a great tool during remote diagnosis and counseling in the hands of trained professionals. But it could also be used to record, analyze and track people’s emotional state in public venues: in front of advertising panels, as well as courtrooms or even job interviews. It can help overloaded elementary school teachers better decipher the emotional state of at-risk children. But it can also lead focus-group obsessed movie studios to further mechanize character and plot development.

The GPU in our computers is the ideal matrix-vector processing tool to decode facial expressions in real-time in the very near future. It would be highly conceivable, for instance, for a presidential candidate to be peering into his teleprompter to see a rolling score of a million viewers’ reactions, passively recorded and decoded in real-time, allowing him to modulate his speech in synchronicity with that real time feedback. Would that be truly “representative” democracy or abdication of leadership?

And if these are possible or even likely scenarios, why wouldn’t we have the technology embedded in a Google Glass-like device or an iPhone 7, available all the time and everywhere. If we can use these gadgets to decode other people’s emotional state, why can’t these gadgets use the same to decode our own and display them back to us? What happens when, for the first time in homo sapiens history, we have constant (presumably unbiased) feedback on our own emotions? The distance from detecting emotional state by machines to suggesting (and even administering) emotion altering medicine can’t be that far, can it? How do we learn to live with that?

The technology is out there. From Apple’s Siri, Google already has the blueprint to advance Google Now from searching to transactions. One would think the recent hiring of Singularity promoter Ray Kurzweil as director of engineering points to much higher ambitions. Ambitions we’re not remotely prepared to parse yet. Much closer to that creepy line.

What’s broken, patents or the legal system?

Referring to the America Invents Act (AIA), aimed to cull low-quality software, the head of the United States Patent and Trademark Office, David Kappos says:

“Give it a rest already. Give the AIA a chance to work. Give it a chance to even get started.”

He’s mostly reacting to studies that claim patent trolls enabled by USPTO cost the economy upwards of $29 billion annually. While awards vary, what’s constant is the exorbitant cost of litigating patent cases. Large scale cases can easily run into tens of millions, taking months and years.

One way to make sense of this situation is to declare the very notion of (software) patents archaic and indefensible in the 21st century. But what if the problem isn’t the fundamental notion or the general utility of patents, rather the inefficiencies in our legal system?

If the legal costs associated with getting and defending patents were 10X cheaper and the process of adjudication much faster, professional and predictable, would we feel differently about patent claims?

Is Siri really Apple’s future?

Siri is a promise. A promise of a new computing environment, enormously empowering to the ordinary user, a new paradigm in our evolving relationship with machines. Siri could change Apple’s fortunes like iTunes and App Store…or end up being like the useful-but-inessential FaceTime or the essential-but-difficult Maps or the desirable-but-dead Ping. After spending hundreds of millions on acquiring and improving it, what does Apple expect to gain from Siri, at once the butt of late-night TV jokes but also the wonder of teary-eyed TV commercials?

Everyone expects different things from Siri. Some think top 5 wishes for Siri should include the ability to change iPhone settings. The impatient already think Siri should have become the omniscient Knowledge Navigator by now. And of course, the favorite pastime of Siri commentators is comparing her query output to Google Search results while giggling.

Siri isn’t a sexy librarian

The Google comparison, while expected and fun, is misplaced. It’d be very hard for Siri (or Bing or Facebook, for that matter) to beat Google at conventional Command Line Interface search given its intense and admirable algorithmic tuning and enormous infrastructure buildup for a decade. Fortunately for competitors, though, Google Search has an Achilles heel: you have to tell Google your intent and essentially instruct the CLI to construct and carry out the search. If you wanted to find a vegetarian restaurant in Quincy, Massachusetts within a price range of $25-$85 and you were a Google Search ninja, you could manually enter a very specific keyword sequence: “restaurant vegetarian quincy ma $25…$85″ and still get “about 147,000 results (0.44 seconds)” to parse from. [All examples hereon are grossly simplified.]

Linear

This is a directed navigation system around The Universal Set — the entirety of the Internet. The user has to essentially tell Google his intent one. word. at. a. time and the search engine progressively filters the universal set with each keyword from billions of “pages” to a much smaller set of documents that are left for the user to select the final answer from.

Passive intelligence

Our computing devices, however, are far more “self-aware” circa 2012. A mobile device, for instance, is considerably more capable of passive intelligence thanks to its GPS, cameras, microphone, radios, gyroscope, myriad other in-device sensors, and dozens of dedicated apps, from finance to games, that know about the user enough to dramatically reduce the number of unknowns…if only all these input and sensing data could somehow be integrated.

Siri’s opportunity here to win the hearts and minds of users is to change the rules of the game from relatively rigid, linear and largely decontextualized CLI search towards a much more humane approach where the user declares his intent but doesn’t have to tell Siri how do it every step of the way. The user starts a spoken conversation with Siri, and Siri puts an impressive array of services together in the background:

  • precise location, time and task awareness derived from the (mobile) device,
  • speech-to-text, text-to-speech, text-to-intent and dialog flow processing,
  • semantic data, services APIs, task and domain models, and
  • personal and social network data integration.

Let’s look at the contrast more closely. Suppose you tell Siri:

“Remind me when I get to the office to make reservations at a restaurant for mom’s birthday and email me the best way to get to her house.”

Siri already knows enough to integrate Contacts, Calendar, GPS, geo-fencing, Maps, traffic, Mail, Yelp and Open Table apps and services to complete the overall task. A CLI search engine like Google’s could complete only some these and only with a lot of keyword and coordination help from the user. Now lets change “a restaurant” above to “a nice Asian restaurant”:

“Remind me when I get to the office to make reservations at a nice Asian restaurant for mom’s birthday and email me the best way to get to her house.”

“Asian” is easy, as any restaurant-related service would make at least a rough attempt to classify eateries by cuisine. But what about “nice”? What does “nice” mean in this context?

A conventional search engine like Google’s would execute a fairly straight forward search for the presence of “nice” in the text of restaurant reviews available to it (that’s why Google bought Zagat), and perhaps go the extra step of doing a “nice AND (romantic OR birthday OR celebration)” compound search to throw in potentially related words. Since search terms can’t be hand-tuned for an infinite number of domains, this comes into play for highly searched categories like finance, travel, electronics, automobiles, etc. In other words, if you’re searching for airline tickets or hotel rooms, the universe of relevant terms is finite, small and well understood. Goat shearing or olive-seed spitting contests, on the other hand, may not benefit as much from such careful human taxonomic curation.

Context is everything

And yet even when a conventional search engine can correlate “nice” with “romantic” or “cozy” to better filter Asian restaurants, it won’t matter to you if you cannot afford it. Google doesn’t have access to your current bank account, budget or spending habits. So for the restaurant recommendation to be truly useful, it would make sense for it to start at least in a range you could afford, say $$-$$$, but not $$$$ and up.

Therein comes the web browser vs. apps unholy war. A conventional search engine like Google has to maintain an unpalatable level of click-stream snooping to track your financial transactions to build your purchasing profile. That’s not easy (likely illegal on several continents) especially if you’re not constantly using Google Play or Google Wallet, for example. While your credit card history or your bank account is opaque to Google, your Amex or Chase app has all that info. If you allow Siri to securely link to such apps on your iPhone, because this is a highly selective request and you trust Siri/Apple, your app and/or Siri can actually interpret what “nice” is within your budget: up to $85 this month and certainly not in the $150-$250 range and not a $25 hole-in-the wall Chinese restaurant either because it’s your mother’s birthday.

Speaking of your mother, her entry in your Contacts app has a custom field next to “Birthday” called “Food” which lists: “Asian,” “Steak,” and “Rishi Organic White Tea”. On the other hand, Google has no idea, but your Yelp app has 37 restaurants bookmarked by you and every single one is vegetarian. Your mother may not care, but you need a vegetarian restaurant. Siri can do a proper mapping of the two sets of “likes” and find a mutually agreeable choice at their intersection.

So a simple search went from “a restaurant” to “a nice Asian vegetarian restaurant I can afford” because Siri already knew (as in, she can find out on demand) about your cuisine preference and your mother’s and your ability to pay:

Restaurant chain

Mind you, all these series of data lookups and rule arbitrations among multiple apps happen in milliseconds. Quite a bit of your personal info is cached at Apple servers and the vast majority of data lookups in third party apps are highly structured and available in a format Siri has learned (by commercial agreement between companies) to directly consume. Still, the degree of coordination underneath Siri’s reassuring voice is utterly nontrivial. And given the clever “personality” Siri comes with, it sounds like pure magic to ordinary users.

The transactional chain

In theory, Siri’s execution chains can be arbitrarily long. Let’s consider a generic Siri request:

Check weather at and daily traffic conditions to an event at a specific location, only if my calendar and my wife’s shared calendar are open and tickets are available for under $50 for tomorrow evening.

Siri would parse it semantically as:

Chain1

and translate into an execution chain by apps and services:

Chainarrow

Further, being an integral part of iOS and having programmatic access to third party applications on demand, Siri is fully capable of executing a fictional request like:

Transfer money to purchase two tickets, move receipt to Passbook, alert in own calendar, email wife, and update shared calendar, then text baby sitter to book her, and remind me later.

by translating it into a transactional chain, with bundled and 3rd party apps and services acting upon verbs and nouns:

Chain4

By parsing a “natural language” request lexically into structural subject-predicate-object parts semantically, Siri can not only find documents and facts (like Google) but also execute stated or implied actions with granted authority. The ability to form deep semantic lookups, integrate information from multiple sources, devices and 3rd party apps, perform rules arbitration and execute transactions on behalf of the user elevates Siri from a schoolmarmish librarian (à la Google Search) into an indispensable butler, with privileges.

The future is Siri and Google knows it

After indexing 40 billion pages and their PageRank, legacy search has largely run its course. That’s why you see Google, for example, buying the world’s largest airline search company ITA, restaurant rating service Zagat, and cloning Yelp/Foursquare with Google Places, Amazon with Google Shopping, iTunes and App Store with Google Play, Groupon with Google Offers, Hotels.com with Google Hotel Finder…and, ultimately, Siri with Google Now. Google has to accumulate domain specific data, knowledge and expertise to better disambiguate users’ intent in search. Terms, phrases, names, lemmas, derivations, synonyms, conventions, places, concepts, user reviews and comments…all within a given domain help enormously to resolve issues of context, scope and intent.

Whether surfaced in Search results or Now, Google is indeed furiously building a semantic engine underneath many of its key services. “Normal search results” at Google are now almost an afterthought once you go past the various Google and third party (overt and covert) promoted services. Google has been giving Siri-like answers directly instead of providing interminable links. If you searched for “Yankees” in the middle of the MLB playoffs, you got real-time scores by inning, first and foremost, not the history of the club, the new stadium, etc.

Siri, a high-maintenance lady?

Google has spent enormous amounts of money on an army of PhDs, algorithm design, servers, data centers and constant refinements to create a global search platform. The ROI on search in terms of advertising revenue has been unparalleled in internet history. Apple’s investment in Siri has a much shorter history and far smaller visible footprint. While it’d be suicidal for Apple to attack Google Search in the realm of finding things, can Apple sustainably grow Siri to its fruition nevertheless? Very few projects at Apple that don’t manage to at least provide for their own upkeep tend to survive. Given Apple’s tenuous relationship with direct advertising, is there another business model for Siri?

By 2014, Apple will likely have about 500 million users with access to Siri. If Apple could get half of that user base to generate just a dozen Siri-originated transactions per month (say, worth on average $1 each, with a 30% cut), that would be roughly a $1 billion business. Optimistically, the average transaction could be much more than $1 or the number of Siri transactions much higher than 12/month/user or Siri usage more than 50% of iOS users, especially if Siri were to open to 3rd party apps. While these assumptions are obviously imaginary, even under the most conservative conditions, transactional revenue could be considerable. Let’s recall that, even within its media-only coverage, iTunes has now become a $8 billion business.

As Siri moves up the value chain from its original CLI-centric simplicity prior to Apple acquisition to its current status of speech recognition-dictation-search to a more conversationalist interface focused on transactional task completion, she becomes far more interesting and accessible to hundreds of millions of non-computer savvy users.

Siri as a transaction machine

A transactional Siri has the seeds to shake up the $500 billion global advertising industry. For a consumer with intent to purchase, the ideal input comes close to “pure” information, as opposed to ephemeral ad impression or a series of search results which need to be parsed by the user. Siri, well-oiled by the very rich contextual awareness of a personal mobile device, could deliver “pure” information with unmatched relevance at the time it’s most needed. Eliminating all intermediaries, Siri could “deliver” a customer directly to a vendor, ready for a transaction Apple doesn’t have to get involved in. Siri simply matches intent and offer more accurately, voluntarily and accountably than any other method at scale that we’ve ever seen.

Another advantage of Siri transactions over display and textual advertising is the fact that what’s transacted doesn’t have to be money. It could be discounts, Passbook coupons, frequent mileage, virtual goods, leader-board rankings, check-in credits, credit card points, iTunes gifts, school course credits and so on. Further, Siri doesn’t even need an interactive screen to communicate and complete tasks. With Eyes Free, Apple’s bringing Siri to voice controlled systems, first in cars, then perhaps to other embedded environments that don’t need a visual UI. Apple having the largest and the most lucrative app and content ecosystem on the planet with half a billion users with as many credit card accounts would make the nature of Siri “transactions” an entirely different value proposition to both users and commercial entities.

Siri, too early, too late or merely in progress?

And yet with all that promise, Siri’s future is not a certain one. A few potential barriers stand out:

  • Performance — Siri works mostly in the cloud, so any latency or network disruption renders it useless. It’s hard to overcome this limitation since domain knowledge must be aggregated from millions of users and coordinated with partners’ servers in the cloud.
  • Context — Siri’s promise is not only lexical, but also contextual across countless domains. Eventually, Siri has to understand many languages in over 100 countries where Apple sells iOS devices and navigate the extremely tricky maze of cultural differences and local data/service providers.
  • Partners — Choosing data providers, especially overseas, and maintaining quality control is nontrivial. Apple should also expect bidding wars for partner data, from Google and other competitors.
  • Scope — As Siri becomes more prominent, so grow expectations over its accuracy. Apple is carefully and slowly adding popular domains to Siri coverage, but the “Why can’t Siri answer my question in my {esoteric field}?” refrain is sure to erupt.
  • Operations — As Siri operations grow, Apple will have to seriously increase its staffing levels, not only for engineers from the very small semantic search and AI worlds, but also in the data acquisition, entry and correction processes, as well as business development and sales departments.
  • Leadership — Post-acquisition, two co-founders of Siri have left Apple, although another one, Tom Gruber, remains. Apple recently hired William Stasior, CEO of Amazon A9 search engine, to lead Siri. However, Siri needs as much engineering attention as data partnership building, but Stasior’s A9 is an older search engine different from Siri’s semantic platform.
  • API — Clearly, third party developers want and expect Apple someday to provide an API to Siri. Third party access to Siri is both a gold mine and a minefield, for Apple. Since same/similar data can be supplied via many third parties, access arbitrage could easily become an operational, technical and even legal quagmire.
  • Regulation — A notably successful Siri would mean a bevy of competitors likely to petition DoJ, FTC, FCC here and counterparts in Europe to intervene and slow down Apple with bundling/access accusations until they can catch up.

Obviously, no new platform as far-reaching as Siri comes without issues and risks. It also doesn’t help that the two commercial online successes Apple has had, iTunes and App Store, were done in another era of technology and still contain vestiges of many operational shortcomings. More recent efforts such as MobileMe, Ping, Game Center, iCloud, iTunes Match, Passbook, etc., have been less than stellar. Regardless, Siri stands as a monumental opportunity both for Apple as a transactional money machine and for its users as a new paradigm of discovery and task completion more approachable than any we’ve seen to date. In the end, Siri is Apple’s game to lose.