sábado, 15 de septiembre de 2018

Resumen–comentario de "Tecnología vs Humanidad" (por @respla para @sintetia)

Tecnología vs Humanidad de Ger Leonhard: ¿con o contra? – @Sintetia otra interesante entrada que no os debéis perder en su totalidad…

Extractos a continuación (con énfasis míos):
…nos encontramos en un punto de inflexión para la humanidad. Un momento crítico creado por los cambios tecnológicos acelerados que vivimos, y sobre todo en lo relativo a lo digital.

…define tres características comunes que tienen este tipo de tecnologías transformadoras:
1.- Exponencial: Los avances tecnológicos siguen curvas parecidas a las de la Ley de Moore. Esto genera un reto cognitivo enorme a los seres humanos ya que nosotros seguimos formas lineales de aprendizaje.
2.- Combinatorio: Las tecnologías se están combinando y convergiendo entre sí para conseguir avances aún más rápidos.
3.- Recurrente: Hay tecnologías que aprenden por sí mismas y que cada vez necesitan menos de humanos para su mejora. 
A su vez, Leonhard describe los 10 megacambios tecnológicos que estamos viviendo en la actualidad, cambios fruto de la convergencia entre tecnologías exponenciales que se están desarrollando simultáneamente: 
  1. Digitalización: Todo lo que pueda ser digitalizado, será digitalizado  
  2. Movilización: Sin cables, móvil y siempre conectado. Esto nos lleva también a que todo se graba.
  3. Pantallización: Revolución de los interfaces.
  4. Desintermediación: Capitalismo de plataformas.
  5. Transformación: La verdad detrás del término ya vacuo de “transformación digital”.
  6. Inteligización: Las cosas se están volviendo inteligentes.
  7. Automatización: Cuando las cosas son inteligentes, luego se automatiza.
  8. Virtualización: Crear una versión digital de todas las cosas.
  9. Anticipación: Las máquinas nos ayudarán a predecir como nunca antes
  10. Robotización: La materialización de todo esto

Leonhard considera que hay cinco etapas en el proceso por el cual vamos cediendo protagonismo a las máquinas, primero en las acciones y luego en las decisiones. Estas cinco etapas son: 

  1. Automatización: Exponencial e inevitable. Pero, ¿debería esta eficiencia realmente prevalecer sobre la humanidad? ¿Deberíamos automatizar las cosas por el simple hecho de que podamos hacerlo?   
  2. Asentimiento: La aceptación de sistemas que nos sustituyen en determinadas acciones porque nos lo hacen fácil y cómodo. Por ejemplo, utilizar sistemas que escriben mensajes por nosotros. 
  3. Abdicación: Renunciamos a hacer cosas que eran de nuestra responsabilidad y las delegamos en máquinas. Confiamos ciegamente en las recomendaciones de las máquinas. 
  4. Agravio: Discriminamos a los seres humanos frente a las máquinas o frente a seres humanos “aumentados”. 
  5. Abominación: El momento de la despersonalización total en el que ya no vemos otras personas sino que vemos números, recomendaciones y evaluaciones dadas por máquinas. 

Por supuesto que el autor se sitúa en el campo humanista y sus propuestas en este ámbito son la parte central del libro. De esta manera, Leonhard advierte de sustituir lo que nos hace humanos, los “androritmos”, por algoritmos lo cual pone en peligro nuestra humanidad. 
En esta línea sugiere reforzar el CORE (creatividad/compasión, originalidad, reciprocidad/responsabilidad y empatía) frente al empuje de las STEM (ciencia, tecnología, ingeniería y matemáticas). Estos androritmos entroncan también con la ética, algo que en principio no sabemos si las máquinas podrán desarrollar algún día. 

Creo que la reflexión más importante del libro se sitúa alrededor de la felicidad. Aporta una afirmación muy interesante: el objetivo principal del progreso tecnológico debería ser la búsqueda de la máxima felicidad humana. Este gran objetivo trae consigo la gran pregunta: qué es la felicidad. 
Se suele hablar de dos tipos de felicidad, la hedonista y la eu̯dai̯monía. La primera es la del ahora y la de los placeres. La segunda tiene más que ver con la prosperidad. 

El psicólogo Martin Seligman utiliza el modelo PERMA para hablar de la verdadera felicidad que no viene sólo de placeres externos y momentáneos: 

  • Pleasure (placer): comida sabrosa, baños calientes. 
  • Engagement (compromiso): Participar en actividades desafiantes. 
  • Relationships (relaciones): los vínculos sociales han mostrado ser un indicador extremadamente confiable de la felicidad. 
  • Meaning (sentido): una búsqueda percibida de pertenencia a algo más grande que nosotros mismos. 
  • Accomplishments (logros): haber alcanzado metas tangibles.
Corremos un riesgo importante de que la tecnología evolucione tanto como para simular toda estas fuentes de felicidad hasta tal punto que no podamos distinguirlas de la realidad.  

El autor acaba el libro con algunas predicciones que dibujan un mundo distópico y que parecen realizables viendo el estado actual de la tecnología y su posible evolución, así como con la recomendación de la formación de un Consejo Global para la Ética Digital (CGED) con la tarea de definir cuáles serían las reglas base y los valores más primordiales y universales que una sociedad tan radicalmente diferente y digitalizada debería tener. 

Para apoyar este CGED y comenzar un debate sobre el tema de la ética digital, el autor habla de un futuro manifiesto que impulsara su creación, para el que propone cinco derechos fundamentales: 

  1. El derecho a seguir siendo naturales, esto es, biológicos.
  2. El derecho a ser ineficientes si esto define, o cuando defina, nuestra humanidad básica. 
  3. El derecho a desconectarnos. 
  4. El derecho a ser anónimos. 
  5. El derecho a emplear o involucrar a personas en lugar de máquinas.

domingo, 9 de septiembre de 2018

China Is Quickly Becoming an AI Superpower (by @singularityhub)

Propelled by an abundance of government funds, smart infrastructure overhauls, leading AI research, and some of the world’s most driven entrepreneurs, China’s AI ecosystem is unstoppable.


As discussed by Kai-Fu Lee in his soon-to-be-released book AI Superpowers, four main drivers are tipping the balance in China’s favor… 
1. Abundant dataPerhaps China’s biggest advantage is the sheer quantity of its data. Tencent’s WeChat platform alone has over one billion monthly active users. That’s more than the entire population of Europe. 
Take mobile payments spending: China outstrips the US by a ratio of 50 to 1.
…While the US saw $112 billion worth of mobile payments in 2016, Chinese mobile payments exceeded $9 trillion in the same year.   
 
2. Hungry entrepreneurs empowered by new toolsFormer founder-director of Google Brain Andrew Ng noted the hunger raving among Chinese entrepreneurs: “The velocity of work is much faster in China than in most of Silicon Valley. When you spot a business opportunity in China, the window of time you have to respond is very short.” 
But as China’s AI expertise has exploded, and startups have learned to tailor American copycat products to a Chinese audience, these entrepreneurs are finally shrugging off their former ‘copycat’ reputation, building businesses with no analogs in the West.
 
3. Growing AI expertiseIt is important to note that China is still new to the game. When deep learning got its big break in 2012—when a neural network decimated the competition in an international computer vision contest—China had barely woken up to the AI revolution. 
But in a few short years, China’s AI community has caught up fast. While the world’s most elite AI researchers still largely cluster in the US, favoring companies like Google, Chinese tech giants are quickly closing the gap. 
Already in academia, Chinese AI researchers stand shoulder-to-shoulder with their American contemporaries. At AAAI’s 2017 conference, an equal number of accepted papers came from US- and China-based researchers. 

4. Mass government funding and supportThe day DeepMind’s AlphaGo beat top-ranking Chinese Go player Ke Jie has gone down in history as China’s “Sputnik Moment.” 
Within two months of the AI’s victory, China’s government issued its plan to make China the global center of AI innovation, aiming for a 1 trillion RMB (about $150 billion USD) AI industry by 2030.

lunes, 27 de agosto de 2018

The Startup vs Enterprise QUEST (by @saranormous via @greylockvc)

 Startups Serving The Enterprise: – Greylock Perspectives



Building strong partnerships and capabilities means that getting out of the marketing swamp, through the winds of cost and risk, across the enterprise feasibility gap, through the desert of procurement and over the ocean of early execution — will all be more tenable the second time around, and the rewards even richer on both sides.

Why are large enterprises so interested in startup tech? It’s a matter of survival. Every company is undergoing a digital transformation. Farsighted executives see the pace of change in business accelerating. These executives know that the companies who more rapidly adopt advancing technology will run their companies better, faster, cheaper, smarter. Technology is a weapon used to defend against competitive threats, and achieve and preserve market dominance.

Similarly, for an enterprise technology startup to survive and thrive, they must understand how to effectively work with large companies. Within large enterprises are most of the employees, data, workflows, industry and institutional knowledge, assets, customer relationships, intellectual property, and budgets in the world.


1. Recruiting Partners in the Swamp of Marketing Fog
Before enterprise executives and startup founders are ready to set sail together, they need to identify the right partners.

  • Shine a Bright Light: A warm introduction can be vital.
  • Paint a Clear (and Easy) Path Out: Startups need to clearly explain the problem they are solving, their value proposition, and their differentiation.
  • Seek the Right Stakeholders, at the Right Time: And those other technologists and leaders are structurally more aggressive in technology adoption than the CIO.

2. Maintaining Faith through the Galewinds of Cost and Risk
One enterprise tech leader said that talking to his team about bringing in a new technology inevitably triggers an immune defense reaction: New vendors need to understand how customers are measuring return and cost. 

Even once your team has cleared a path out of the swamp, it can feel like you’re fighting against a galewind. There’s a lot of natural resistance to bringing in new vendors, because a new offering needs to be valuable enough to overcome inherent cost and risks of working with a startup.

Startups should be empathetic to this risk aversion and understand that, on the customer side, someone’s career is often on the line.

Enterprise customers told us they think also about the “hidden costs” of vendor management, user training and adoption, integration, implementation and administration, and the risk of the startup dying or getting acquired.
Because of these many “hidden” costs, smart technology buyers are projecting out the landscape of vendors, and looking for startups that not only offer tactical benefits but have a chance to endure as longer-term partners — disrupting an existing category or creating an important new one.
Advantages for disruptor companies include innovating on the experience of purchasing and using the technology, and the total cost of ownership.

To de-risk their decisions, enterprise tech leaders want to work with startups that have raised capital from top-tier investors, because it’s one sign they’ll go the distance.


3. Bridging the Gap of the Four S’s: Scale, Security, Spend & Supportability
Value may outweigh the costs and risk, but will the product work in their environment?

  • Scale: Can the startup support the scale of the customer’s user base or infrastructure? Increasingly, we see customers want to validate that scale rather than taking it on faith. … This includes ease of use, rollout plan, reporting, integrations into existing technology, administration workflows, SLA’s. Customers are also evaluating who is going to help them deploy — for example, the existence and quality of the startup’s sales engineering or implementation team, if needed.
  • Security: Startups told us this is #1 on everyone’s list. The need is often driven by regulation such as GDPR, or internal requirements for sophisticated access control, and the key thing here is to have a clear approach to customer data.
  • Spend: Pricing models that are appropriate for the first thirty developers or first hundred users might not work for broad deployment. Startups must offer pricing models that are feasible at scale, aligning with the value they create for their customers.
  • Supportability: Is the startup prepared to offer the kind of support (often 24/7) that enterprise customers need, at scale? Can they handle the reality of legacy technology that large companies are often saddled with, and make their customer successful?

4. Avoiding the Quicksands of Customization

The quicksands of customization are an especially tricky neighborhood.
…getting sucked into customization can mean company death, or at least, derailment.

Just as customers will choose to work with a particular startup based on ability to scale, durability, and other factors, startups should also choose their early customers carefully, balancing customer requirements against strategic priorities and limited company resources. Being too accommodating or diffuse in strategy can be a recipe for mediocrity in multiple categories.
Disciplined customer segmentation is key

Giving potential customers realistic visibility into your short and medium term roadmap is also a pattern for success. Beyond choosing early customers carefully, startups should also take a pragmatic view of what feature requests to field, and when.


5. Surviving the Desert of Procurement & Approvals
The procurement process can be a bear — you feel like you’re so close to the finish line, but it’s a mirage. You can get stuck in limbo.
Startups need to have realistic expectations about speed, and plan ahead for sales cycles so they don’t run out of resources before they show progress.
Enterprises, on the other hand, need to create pathways for the business to push through important innovations fast.

To accelerate their sprint through the procurement and legal desert, startups should find internal champions, arm those buyers with the right business case and other support, and arrive prepared with mature contracts.
There are also different purchasing processes for different scales of spend. Building up engagement with a large enterprise partner through a land-and-expand model also changes a startup’s initial experience in procurement.


6. Crossing the Ocean of Early Execution
Finally, quest-goers need to build a strong ship and chart a clear course to cross the ocean of early execution.

  • First, this means structuring PoCs and initial engagements to be short, with repeatable onboarding flow, clear success criteria and commitment from partners to that timeline.
  • Second, technology leaders also cautioned against “poisoning the well” — damaging relationships and reputation by not delivering on promises.
  • Third, enterprises need startups to consciously involve the necessary stakeholders to operationalize technology, even in planning and deployment, support their change management, and follow up with discipline.

7. The Golden Fields of Innovation

In summary, the quest to reach the golden fields of innovation — that is, to successfully deploy new capabilities and technologies into the enterprise — is a journey that requires strategy, careful planning and consistent execution.
Once that early execution is successful, this is not a one-time quest. It’s an ongoing journey with each new partner, and each new use case and product line. An early success lays the groundwork for a strong customer reference that will help generate new business — in today’s age of connectedness and transparency, a startup’s best salespeople are its happy customers.

domingo, 26 de agosto de 2018

With Greed and Cynicism, Big Tech is Fueling Inequalities in America (by @filloux)

With Greed and Cynicism, Big Tech is Fueling Inequalities in America – Monday Note, Frederic Filloux

…In the end, local taxpayers will subsidize Amazon shareholders…

Hi-tech firms are prominent among recent tax-break “megadeals” awarded by cities and states. Tesla’s battery factory ($1.3bn from Nevada), Foxconn’s display-screen plant in Wisconsin ($4.8bn) and Apple’s data centre in Iowa ($214m) are typical. The Apple centre, a cloud computing facility, will have only 50 permanent jobs, so the cost per job exceeds $4.2m. The Foxconn deal, even by the state’s own official estimate, won’t break even for taxpayers for 25 years — an extremely risky time horizon given the likelihood of new technologies leapfrogging the company’s product much sooner. The Tesla deal was 14 times costlier than anything Nevada had done before.

5 online-luxury-fashion trends (by @forbes via @wealthx)

  What Farfetch's IPO Filing Says About The $300 Billion Luxury Fashion Industry – Wealth-X



1. By 2025, luxury fashion e-commerce will have a quarter of the industry's market share. 

Industrywide, online’s share of the personal luxury goods market is expected to rise to 25% by 2025 from about 9% last year as the entire market pie will see 45% growth to $446 billion over the same period, from $307 billion last year, Farfetch said in the filing, citing a Bain & Co. study.


2. Yes, credit or (blame) Millennials, and soon Gen Z.

By 2025, the two groups combined, mostly led by Millennials, will represent 45% of total luxury spending. That will beat the 40% share expected to be held by Gen Xers


3. Democratization of luxury fashion?

…online sales have leveled the playing field for young brands seeking access to consumers, marketplaces are giving smaller luxury brands and boutiques a bigger opportunity to reach a global consumer base.ç


4. Data science is hot.

“We are a technology company at our core. We operate at the intersection of luxury fashion, online commerce and technology." (Farfetch)
What kind of data does it have? real-time inventory data, global behavioral and transactional data and pricing data for over 335,000 SKUs (unique units) from more than 3,200 different brands…


5. Growth at the cost of profit may be the new norm.

Amazon’s years-long model of investing behind growth before it finally turned a profit looks to be increasingly popular among companies eyeing online growth and seems to be accepted by investors.

Arquitectura y tecnología – Mies van der Rohe, 1950

 tal como aparece en "Conversaciones con Mies van der Rohe", de Ed. Gustavo Gili, ed. Moisés Puente)


La tecnología tiene sus raíces en el pasado.
Domina el presente y tiende al futuro.
Es un verdadero movimiento histórico;
uno de los grandes movimientos que dan forma y
representan su época.
Sólo puede compararse con el descubrimiento clásico
del hombre como persona,
con la voluntad de poder de los romanos
y con el movimiento religioso de la edad media.
La tecnología es mucho más que un método;
es un mundo en sí misma.
Como método, es superior en casi todos los aspectos.
Pero sólo allí donde se la deja sola, 
como en la construcción de maquinaria
o en las gigantescas construcciones ingenieriles,
la tecnología revela su verdadera naturaleza.
Ahí se hace patente que no sólo es un medio útil,
que es algo, algo en sí misma,
algo que tiene un significado y una forma poderosa;
tan poderosa, de hecho, que no es fácil ponerle nombre.

¿Es eso aún tecnología, o es arquitectura?

Esta puede que sea la razón por la que alguna gente
está convencida de que la arquitectura quedará anticuada
y será reemplazada por la tecnología.
Tal convicción no se fundamenta en ideas claras,
sino todo lo contrario.
Donde la tecnología alcanza su verdadero cumplimiento,
va más allá de la arquitectura.
Es cierto que la arquitectura depende de hechos,
pero su verdadero campo de actividad se encuentra
en el terreno de la trascendencia.
Espero que entiendan que la arquitectura
no tiene nada que ver con la invención de formas.
No es un campo de juegos para niños, jóvenes o mayores.
La arquitectura es el verdadero campo de batalla del espíritu.
La arquitectura escribió la historia de las épocas
y dio a éstas sus nombres.
La arquitectura depende de su tiempo.
Es la cristalización de su estructura interna,
el lento despliegue de su forma.
Esta es la razón por la que la tecnología y la arquitectura
están tan estrechamente relacionadas.
Nuestra verdadera esperanza es que crezcan juntas,
que algún día una sea la expresión de la otra.
Sólo entonces tendremos una arquitectura digna de su nombre:

una arquitectura como un símbolo verdadero de nuestro tiempo.

sábado, 18 de agosto de 2018

Unicorns, Cheshire Cats, and the New Dilemmas of Entrepreneurial Finance (by BRIE from @UCBerkeley)

Interesting report on the "new economy" by BRIE, Berkeley Roundtable on the International Economy.



It is difficult to be certain which of the changes we describe are permanent and which are transient. The technical changes that are easing entry seem to be part of a permanent environmental change. The technical diminution of entry barriers, however, may be balanced by the remarkable power of the incumbent platform giants. Effectively, the preponderance of these new entrants may be subsumed into the platform giant’s ecosystem and thus face constrained growth opportunities. Exactly what the ultimate balance will be is difficult to predict. 
While, the technological changes and the tensions between eased entry and platform power to control ecosystem complementors can be expected, the changes in the financial sector are far more opaque. For example, if there is a financial crisis, such as those in either 2000 or 2008, which types of financial intermediaries will continue to be active in funding startups? Will angels and accelerators still have sufficient capital, and, if as is likely, only the best ones survive, what will be the implications for the enormous number of startups currently operating? Even more uncertain is whether the organizations that have been providing funding for the later growth phases, where large sums of capital are required, will continue their support. The situation would become particularly precarious if the IPO and acquisition markets were to freeze up simultaneously, as these private investors would be called upon to commit capital at the very time when they were experiencing a capital squeeze. From a political economic perspective, because in most of these firms the assets are largely software and data, liquidations are likely to be nearly total with little residual value remaining.Oddly, our conclusion is contradictory. The powerful transformative forces currently at work driven by the move to a platform-centric economy appear to be inexorable. And yet, the capital necessary to nurture many of these transformative firms is dependent upon a robust flow of capital, particularly since as we demonstrated, IPOs as exits have declined markedly and did not recover significantly despite the passage of the JOBS Act. If these alternative sources of capital are no longer available and the capital markets are closed, then the startups that do have significant potential will be forced to either sell themselves to the platform giants or fail outright. The implications are that the incumbents will be able to purchase the firms that Schumpeter suggested would replace the existing firms. 
It is symbolic of global acceptance that the Silicon Valley model for innovation and entrepreneurship exemplified by its capture by one dominant form of entrepreneurship, the venture- backed Unicorn, is the best type of firm to be supported and such entrepreneurship is a path equally available to all. This model is embraced by both local governments and educational institutions as an optimal economic development goal. The result has been a proliferation of accelerators, incubators, entrepreneurship courses and programs, etc., that themselves lower start-up entry barriers, thus reinforcing the phenomenon of competitive commoditization. This narrative advances the view that the venture-backed startup – in reality, a narrow class of startups that can quickly grow to a large scale over a decade or less is the most desirable model. 
This essay calls those conclusions into question.

sábado, 11 de agosto de 2018

¿Cómo hacer una empresa atractiva para el talento? ( by @KPMG_ES )

¿Cómo hacer una empresa atractiva para el talento? - KPMG Tendencias?

Hay varios factores que inciden entre los elementos que hacen que una organización sea atractiva en el mercado laboral y que van desde los valores y la cultura de la empresa; al contenido y los retos que suponen ese empleo; las políticas de remuneración y de reconocimiento y desarrollo profesional y, por último, aunque no menos importante, el entorno de liderazgo y personas que uno se va a encontrar.


Profesionales más comprometidos
Las compañías que han desarrollado una Propuesta de Valor para el Empleado atractiva y efectiva tienen profesionales más comprometidos con la organización. Eso se traduce en menos rotación laboral, más innovación, mayor productividad, niveles más altos de satisfacción de clientes, crecimiento de la cuota de mercado de la compañía y mayores beneficios para la organización…

Los datos son impresionantes: las compañías con mayor engagement consiguieron un aumento del 65% de su valor en bolsa20% menos de absentismo15% más de productividad30% más de satisfacción de clientes y un 100% más de recepción de currículos. Diversos estudios confirman el impacto positivo de un mayor compromiso laboralen los ingresos y resultados de la compañía.

Propuesta de Valor para el Empleado
  1. El propio puesto de trabajo y su contenido
  2. La alineación de los valores de la organización con los del empleado.
  3. El liderazgo de la primera línea y las personas con las que trabajo.
  4. La remuneración y el reconocimiento en sentido amplio.
La Propuesta de Valor para el Empleado (PVE) abarca toda la experiencia del empleado, antes de su incorporación a la compañía, durante su permanencia en la misma y tras su salida de la organización.

…no contar con una buena Propuesta de Valor para el Empleado realmente atractiva, con todo lo que ello implica, tiene un coste cada día más elevado. Uno, fácil de cuantificar, el coste de reemplazar a los que se marchan–se estima entre el 50% y 150% del salario anual del nuevo empleado– y otros, no tan sencillos de cuantificar, tiene que ver con el déficit de talento que puede sufrir la compañía, la desmoralización interna, la falta de compromiso de los empleados, el impacto potencial en la relación con clientes y en la marca como empleador



sábado, 4 de agosto de 2018

The 70-20-10 Rule for Leadership Development

The 70-20-10 Rule for Leadership Development



A research-based, time-tested guideline for developing managers says that you need to have 3 types of experience, using a 70-20-10 ratio: challenging assignments (70%), developmental relationships (20%), and coursework and training (10%).
The 70-20-10 rule emerged from 30 years of our research, which explores how executives learn, grow, and change over the course of their careers.
The underlying assumption is that leadership is learned. We believe that today, even more than before, a manager’s ability and willingness to learn from experience is the foundation for leading with impact.
The 70-20-10 rule seems simple, but you need to take it a step further.

domingo, 15 de julio de 2018

Shouldn't we be investing more in quantum computing? (by @azeem )

Exponential View #174 – Dept of quantum computing

BCG report

Given the large potential of quantum computing, the actual investment levels are low (with one exception, see at the end of this). We reckon, from a rough LinkedIn count, that fewer than 2,000 people are involved in companies working in any part of the quantum stack (and that includes all the marketing and PR types attached to these groups in large companies). IBM Q, which runs a developer ecosystem via the IBM Quantum Experience API, should have the deepest team. My scan on LinkedIn (far from perfect) shows only 300-or-so names attached to quantum computing in all of IBM. The startups are of similar scale, Rigetti, numbering less than 150. 
Some estimates go beyond this. There are 7,000 researchers working on quantum computing around the world, a more healthy but still small number, according to the European Commission. 
The venture dollars flowing intro quantum computing is small with D-Wave ($175m), Rigetti ($70m), Cambridge Quantum Computing ($50m) and IonQ ($20m) leading the pack. The European Commission further estimates that total global annual investment in quantum research is some €1.5bn per annum. (Deloitte has further estimates: suggesting that there is about $2.2bn investments globally by governments in quantum computing.) 
So quantum computing is Schrodinger’s opportunity, simultaneously here and not here at the same time. 
On the one hand, quantum computing is getting all the accoutrements of a technology close to maturity (press briefings, Gartner reports, analysis from investment banks and management consultancies) and the large tech firms are trumpeting working systems within 5 years. 
On the other, investment levels are tiny by the standards of what large companies can put to work, or what VCs invest (Wag, a dog-walking app, recently raised $300m.) This suggests that these smart investors are discounting the potential upside very heavily, i.e. there are many hurdles, which these investors cannot easily enumerate, to overcome or the time frame to realise is very long.
Which is it? Close to maturity or facing a long journey? 

Only two years ago, I was pretty sceptical about where quantum computing was in its cycle. And as Jerry Neumann points out, quantum computing was only “five years away” back in 2000, so quantum could be one of those technologies, like controllable fusion, that is always just around the corner.