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.

China Is Quickly Becoming an AI Superpower

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.

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.

A Look at How Technology is Reshaping the Global Economy (by @maxmarmer )

 via medium – The Industrial Era jobs and institutions decline towards death and the Information Era matures and blooms. The decline of the Industrial Era may have been subtler, and easy to ignore in years past.

The global economy as a whole will also be in precarious place if Information Era companies do not continue to produce accelerating growth. While we’ve nominally been in recovery since 2009, much of the expansion has been enabled by unprecedented levels of debt created by Central Banks around the world. Sky high debt levels across consumers, corporations and countries, are all being buoyed by historically low interest rates. Wealth inequality is rising fast and geopolitical tensions are heating up. We’ve been blessed by very low volatility the last few years, but we also are in many ways dependent on it.

Technology companies continue to become a bigger percentage of the world economy. They have overtaken Oil and Gas companies to become the largest public companies in the world, the private market is bursting with billion dollar unicorn valuations unseen before in history, and many non-technological industries are either dying at its hands or becoming one with it.

Some of this technological future will come from large companies, but by and large these large companies still haven’t figured out how to reliably create disruptive innovation. Their role in the innovation landscape is predominantly as acquirers, where they grow acquired products, applying their capacity for efficiency and scale.

An essential orienting frame for understanding the current state of the world, is that we are at a point of criticality. A liminal space between eras. The old world Industrial order is breaking down, and the new Information world order is in the process of taking over. This transition period is one of opposing forces of exponential creation and exponential destruction.

In the forthcoming era of technological disruption the need for a robust social safety net will be paramount.


worth reading, I'd recommend max. attention ;-)

How To Become A Centaur (by @ncasenmare)

 AIs are best at choosing answers. Humans are best at choosing questions.
via @mit_jods How To Become A Centaur by Nicky Case

…we’ve told ourselves that our relationship between ourselves and our AI is like a chess game: 

Zero-sum — one player’s win is another player’s loss.

…
They invited all kinds of contestants — supercomputers, human grandmasters, mixed teams of humans and AIs — to compete for a grand prize.²

Not surprisingly, a Human+AI Centaur beats the solo human. But — amazingly — a Human+AI Centaur also beats the solo computer.

This is because, contrary to unscientific internet IQ tests on clickbait websites, intelligence is not a single dimension. (The “g factor”, also known as “general intelligence”, only accounts for 30-50% of an individual’s performance on different cognitive tasks.³ So while it is an important dimension, it’s not the only dimension.) For example, human grandmasters are good at long-term chess strategy, but poor at seeing ahead for millions of possible moves — while the reverse is true for chess-playing AIs. And because humans & AIs are strong on different dimensions, together, as a centaur, they can beat out solo humans and computers alike.

…
Now, not only does pairing humans with AIs solve a technical problem — how to overcome the weaknesses of humans/AI with the strengths of AI/humans — it also solves that moral problem: how do we make sure AIs share our human goals and values?

And it’s simple: if you can’t beat ‘em, join ‘em!

The rest of this essay will be about AI’s forgotten cousin, IA: Intelligence Augmentation. The old story of AI is about human brains working against silicon brains. The new story of IA will be about human brains working with silicon brains. As it turns out, most of the world is the opposite of a chess game:

Non-zero-sum — both players can win.

…I’ll show how humans are already working with AIs in various fields, from art to engineering. And finally, I’ll give some rough ideas on how you can design a good partnership with an AI — how to become a centaur. 

Together, humans and AI can go from “checkmate”, to “teammate”.

Over the next few decades, the wonders in The Mother of All Demos slowly reached the public. The personal computer gave ordinary people the power of computing, something only governments and big corporations could afford previously. A particle physics lab in Switzerland released a little thing called the “World Wide Web”, which let people share knowledge using things called “web pages”, and people could even create connections between pieces of knowledge using something called a “hyperlink”.

Steve Jobs once called the computer a bicycle for the mind. Note the metaphor of a bicycle, instead of a something like a car —a bicycle lets you go faster than the human body ever can, and yet, unlike the car, the bicycle is human-powered. (Also, the bicycle is healthier for you.) The strength of metal, with a human at its heart. A collaboration — a centaur.

Doug Engelbart envisioned that the computer would be a tool for intellectual and artistic creativity; now, our devices are designed less around creation, and more around consumption. Forget AI not sharing our values — even non-AI technology stopped supporting our values, and in some cases, actively subverts them.⁷

We hoped for a bicycle for the mind; we got a Lazy Boy recliner for the mind.

…

When you create a Human+AI team, the hard part isn’t the “AI”. It isn’t even the “Human”. 

It’s the “+”.

…

Human nature, for better or worse, doesn’t change much from millennia to millennia. If you want to see the strengths that are unique and universal to all humans, don’t look at the world-famous award-winners — look at children. Children, even at a young age, are already proficient at: intuition, analogy, creativity, empathy, social skills. Some may scoff at these for being “soft skills”, but the fact that we can make an AI that plays chess but not hold a normal five-minute conversation, is proof that these skills only seem “soft” to us because evolution’s already put in the 3.5 billion years of hard work for us.

And if you want to see the weaknesses of humans, go to school. This is the stuff that’s hard for human intelligences, and requires years of training to gain even a basic competency: arithmetic, computation, memory, logic, numeracy. Note that these are all things your phone can do better and faster than the smartest human alive. (And we wonder why kids feel school is meaningless…)

AIs choose answers. Humans choose questions. And given all the possibilities, the promises and pitfalls of technology in the coming decades, the next question for us humans to choose is:

What’s next?

Meanwhile, the story of IA has been one of a tragic fall. Starting out strong with Doug Engelbart’s Mother of All Demos, the idea of IA has slowly been forgotten, as technology shifted from tools for creation and more towards tools for consumption. Someone stole the wheels off the bicycle for our mind.

But now, these two story threads may be starting to wrap together, forming a new braid in history: AIA — Artificial Intelligence Augmentation.⁸ IA can give AI the human partnership it needs in order to remain aligned with our deepest goals and values. And in return, AI can give IA some new replacement wheels for the bicycle of our mind.

I’d like to tell you what the future holds. But if you tell someone something good is inevitable, it can cause self-defeating complacency — and if you tell someone something bad is inevitable, it can cause self-fulfilling despair.

Besides, answers are for AIs. As a human, you deserve questions.

Symbiosis shows us you can have fruitful collaborations even if you have different skills, or different goals, or are even different species.  Symbiosis shows us that the world often isn’t zero-sum — it doesn’t have to be humans versus AI, or humans versus centaurs, or humans versus other humans. Symbiosis is two individuals succeeding together not despite, but because of, their differences. Symbiosis is the “+”. 

A new chapter in humanity’s story is beginning, and we — living together — get to write what happens next.

9 frameworks to master Product Management (by @firstround)

 #mustread … The best companies are most often built by extraordinary product minds. Even if you’re not a PM right now, you can benefit from adopting the habits and strategies that make talented PMs successful.

17 Product Managers Who Will Own the Future of NYC Tech — and the 9 Frameworks They’ll Use to Do It | First Round Review

Absolute must read

1. Getting into the PM Mindset
A good PM fills in the gaps and gets out of the way.
Prioritization becomes critical. 
Significance = Magnitude x Number of People Impacted
where magnitude is a measure of how frustrating/painful/unbearable the problem being solved is.
A magnitude 1 problem might cause mild annoyance, whereas a magnitude 3 problem might cause show-stopping frustration and anger.

Continually question whether the tactic you’re trying creates more friction than the original problem. If the answer is yes, immediately shift course.


2. Figuring Out When to Build What
-Time-Based Risk: when a competitor has launched a new version of its product that its customers don’t like as much, that would give you a time-window.
-Building Blocks First: the other follow-up question you should always ask is “How many other projects depend on this thing?”


3. Turning Product Vision into an Executable Strategy
-Structure your vision wisely.
-Create 2-3 objectives that move you toward that vision.
-Place bets under each objective.

Following this template, you end up with a quarterly roadmap that has every action and each person’s work closely connected with the company’s direction and purpose.


4. Effective Stakeholder Communication
Group 1: Executives and leadership
Do...
-Send presentations, decks and other materials before every meeting.
-Validate every decision with data.
-Be specific about the executives' desired participation.
-Take notes and close the loop.
-Send high-level updates right after each meeting with action items.
Don’t...
-Go into too much detail.
-Surprise anyone with bad news. If the news is bad, reach out to folks 1:1 in advance.
-Show up unprepared.
-Ignore room dynamics.

Group 2: Your own team
Do...
-Leverage efficient daily stand-ups.
-Review strategy/roadmaps regularly.
-Record and send out notes on key decisions and actions.
-Reward team members often, tell anecdotes about customer pain points that were alleviated.
Don’t...
-Make decisions without engineering and design.
-Send action items/requests without talking about them first, 1:1 or stand-up.
-Forget to update folks on roadmap or specs changes, particularly important after meeting with execs.

Group 3: Internal and external partners
Do...
-Exhibit detailed understanding of their work and domain.
-Use the right format at the right time with the right audience.
-Leverage your teammates. Bring in engineering leads.
-Gently and continuously educate them. Partners sometimes don’t know the consequences of their actions.
-Build relationships outside of work meetings.
-Create transparency. Don’t rely on others to communicate to everyone.
Don’t...
-Forget who to loop in at what stage.
-Make stakeholders feel ignored.
-Forget you have more insight than anyone else. Stakeholders don’t see your roadmap.
-Allow meetings to end without clarity.
-Forget to educate about timelines and tradeoffs.

Group 4: Customers
Do...
-Always start with the user problem. Ask why and understand the journey that creates that pain point.
-Keep, what’s important to them, top of mind.
-Treat email copy as a part of the product experience.
-Generate empathy for yourself by reading through user feedback, attending user studies in person…
Don’t...
-Leave product communications/messaging to the last minute. *Start with this, don’t end with it.
-Assume marketing will position the product themselves.
-Leave customer success in the dark about launch.
-Believe internal products require no roll out.


5. Create Compelling Product Messaging
Start with one question:
What superpower do you want to give your user? For example, the iPhone lets us navigate to unknown places wherever we are in the world. As a PM, it’s your job to ensure the entire team knows the story you’re trying to create for your users. *This should come first in your development process, not last.
Will Carlin’s 5 C’s framework comes in hand for telling strong stories (your goal should be to craft a story around a single user — not a group of users).
-Context: Establish the setting and identity of the user you’re talking to.
-Conflict: The problem your product attempts to solve for that user.
-Conflict Escalation: Really visualize what it’s like for a user to encounter this problem. Draw out the emotions tied to the pain point and solutions that have been tried but failed. Really feel and describe the frustration, disappointment, etc.
-Climax: Your product is introduced — what changes for the user?
-Conclusion: Detailed description of the improvement in the user’s life.

Use this framework to create a story about your product. Remember, no matter what you do, different versions of your story will emerge once it launches. To win, craft the story that is closest and most personal to your user. The more emotionally resonant it is, the more it will drown out competing perspectives.


6. Build Your Best Product Team
You have to hire people who aren’t just talented, but who are perfect for your particular business.
Develop a strategic hiring plan by determining who on your existing team should be a part of the hiring process (all relevant folks the role will interface with), and the concrete steps every candidate will take between application and hire.
-Build a strategic hiring plan.
-Define key competencies
-Standardize your assessment of competencies.
Running this exercise is time intensive. You have to run several voting rounds to arrive at competencies, questions for each competence, and then the best and worst responses to each question. Sounds like a lot, but it’s incredibly worth it to have a standardized approach created collaboratively — one that can be recycled and reused again and again as hiring picks up pace.


7. Scale Yourself as a Product Leader
PMs should focus on scaling in four areas: decision making, velocity, collaboration and empowerment.

Decision making starts to slow down and crack at a certain point of growth. The warning sign is too many cooks in the kitchen and slowed pace. The antidote is the DACI framework:
-Driver: The one person responsible for the project who drives process and keeps everyone aligned.
-Approver: The person who approves the proposal/recommendation for the project.
-Contributors: People working on the project team, providing input, producing work, etc.
-Informed: People kept in the loop about the project and results, but not contributing.

Velocity of work starts to slow down as tech debt accumulates and teams grow. To fix it, create durable teams around durable problems. To avoid scope creep and last-minute design changes, Chang recommends the following product development process:
-Goal definition: Everyone included in your DACI framework should come together and emerge with a singular goal for the product.
-Product definition: Align on scope of the project and what will be required to solve the problem at hand. What is and isn’t out of scope?
-Design review: Be explicit about the type of feedback you want and don’t want.
-Tech review: Make sure everyone has a chance to debate and buy into the technical approach.
-Go/no-go: Review your checklist to make sure the rest of the org is operationally ready for a product/project launch — i.e. customer service has the bandwidth to answer questions, etc.

Collaboration starts to break at a certain company size. Free people up and fuel effective collaboration with these three moves:
-Make your product roadmap and product docs accessible to the entire company.
-Hold Gate Meetings to force decisions that must be made to proceed.
-Send decision emails to communicate to all possible stakeholders when big decisions have been made and why.

Empowerment at scale becomes important when teams get so big that people feel like they’re just executing on other people’s orders. Several strategies to combat this are:
-Present options instead of a firm decision.
-Start milestone meetings with a background share.


8. Drive Product Development with Data
PMs use data to align stakeholders with roadmaps, track efficacy of what's been built, and prioritize what to build next.
-You have to gather implicit data. Stop making excuses. If you don’t, you’ll have no real visibility into how users will react to new features. These can be little experiments, like seeing if someone will click on a link.
-Don’t underestimate the importance of explicit data. Protect yourself against this by taking in qualitative feedback shared directly by your users.
-Always go to your customers when you observe them. see how people are using your product in their natural habitat. If they’ve developed any workarounds, take special note.
-Find the right users for your questions. At B2B companies, product managers often find themselves engaging with the C-suite at their customers. Determine who is the most relevant user of your product, and pose the questions to them directly.
-Find a meaningful metric for your performance. Net Promoter Score is a common choice, but that’s not universally appropriate. You could augment it with a Customer Effort Score —a measure of whether the company made it easier to perform certain tasks.


9. Going from PM to Founder
In many ways, product management is the ideal springboard for founders. It’s a position that affords you opportunities to go deep in areas that will serve you when running your own business, like:
-negotiation
-P&L and forecasting
-legal-
-hiring
-operations

But before you can get into all of that, you need to be sure you’re choosing the right idea to work on.
How do you know if an idea is worth pursuing? Evaluate each one according to Marty Cagan’s Four Big Risks:
-Value: Do people want this? When you talk to prospective users, do they see value in what you’re building?
-Usability: Can people figure your solution or product out intuitively?
-Feasibility: Can you and an eventual team build what you have in mind within a realistic time frame with the resources you can realistically get?
-Viability: Is there a clear business model and path to making money?
Before you set out after an idea, make sure you can check each of these boxes and confidently explain your answers to each of these questions to possible investors.

¿Ha mutado la economía colaborativa en un capitalismo salvaje de plataformas?

 este artículo en El Mundo me ha hecho recordar esta otra entrada en el blog en base a un artículo de HBR.
Es un tema sobre el que ya he tenido alguna conversación, siempre defendiendo que compàrtido no me parece exactamente lo que se vende muchas veces… y que merece una reflexión.
En cualquier caso merece la pena una leída…
¿Ha mutado la economía colaborativa en un capitalismo salvaje de plataformas? – El Mundo - economia/empresas

More than 40 Lessons from 40 Years of Apple Ads

 via @ianfiason from @TheMissionHQ 40 Lessons from 40 Years of Apple Ads – The Mission – Medium

1. When you’re introducing something new, keep it simple.
2. Provide social proof from buyers.
3. Ask for feedback and don’t be afraid to launch weird contests.
4. If there is a reputable national or historical figure from history you can tie your product to, do it.
5. Don’t be afraid of tackling hot button issues if your intentions are good, and your product or service can help
6. Promote a diversity of people and ideas.
7. If you were the first mover with a product or service, tell everyone about it.
8. Pack a powerful Call To Action 
9. Be a bit radical with your ads, but don’t insult people.
10. Distill your message into what your product or service helps people do.
11. If you need to make sales, you need to create a campaign (or content) that will help your sales teams sell.
12. Sometimes those who have been ousted from the company have the best ideas about how to improve it.
13. If you want to create a new market, beware of being too early, and you might have to start advertising it decades in advance.
14. Keep it simple.
15. Pick the broadest misconception that’s stopping people from trying your product or service; show your users how easy trying your product or service could be.
16. How early adopters and trendsetters are using your product or service might be the most interesting thing your ads can depict.
17. The ad exemplifies the importance of explaining what you’re selling through using similes and metaphors.
18. Show what life is like before your product, and what it’s like afterward.
19. Influencer marketing works. Find a macro question your early adopters have, and show them how influencers that speak to them attempt to answer it. … Not just about your product, but about life, too.
20. Product placement works, and if you’re upfront about it, you can build and maintain trust with your audience.
21. Choose to celebrate or associate with celebrities that are famous because of their substance. … If you associate with higher qualities (courage, imagination, creations), your ads will be far more evergreen. People will attack you for your audacity, but at least you’re promoting great role models.
22. Pick out the number one alternative to your product or service. Then show why your product is a better alternative.
23. If you help reduce the level of fear someone has, they’ll be grateful for a long time.
24. Remind your customers that with your product, they can take something they already have to the next level. Show them going from the raw material to a finished product in a minute.
25. If your product or service can help people reach their ideal state, don’t be afraid to show it off.
26. Create an image highlighting the differences in your products. … If they see them as being different, they’ll seek to understand those differences and learn more about your offering.
27. By using a silhouette and many different selections of music, Apple increased their chances that people would individually connect with this ad.
28. When you’re out of ideas, or on a tight budget, repurpose an ad from the past. Apple remastered their 1984 campaign and republished it.
29. Show that your product or service is in demand.
30. If your product or service solves a real need, don’t be afraid to tell people to get it.
31. Suggests that there is a new way to do something you do every day (answer the phone).
32. Pick the one attribute of your product that is most remarkable. Then present it with the right context that helps show how remarkable it is.
33. Think of all the different things people use a feature of your product to achieve, and show them being addressed. It brings up the idea that no matter what your question, we have the answer.
34. Wherever possible, show what your thing can do… Show, don’t tell.
35. Remind people of features that makes your offering unique.
36. Don’t exaggerate or oversell. (This ad pushed the bounds of what Siri could do, irritating some people.)
37. Show how your product or service can be a part of reaching higher ideals.
38. There are certain reminders which we need to hear often. This ad focuses on one, “You’re more powerful than you think.”
39. There is something your potential customers know they need to be doing more of. Show how you can help your customers fight that battle.
40. Once you have a backlog of content, show it all off in a remix.
41. Show people what life would be like in the absence of your product or service.
42. Most people might not get everything out of your product or features that they could. That’s okay, but don’t be afraid to show them what an extreme/fully optimized use case might look like.

is the world coming to an end?

I quote one of the last Peter Diamandis' newsletters… as it sets up the right mindset (in my opinion) to "front facing" the future.

We’re living in a period of rapid change, and over the next 5 years, we’re going to see significant disruptive advancements that will reshape the world as we know it. 

So many people fear change, and because they don’t understand where technology is leading us, they have very gloomy views of what the future holds. 

If you listened to many media pundits, they’d have you believe that the world is coming to an end. 

The data shows others. 

The facts, however show that the world is getting better at an extraordinary rate. 

I truly believe that this is the most exciting time ever to be alive. 

As an entrepreneur, you have access to the world's information on Google. You can go onto Amazon Web Services and have access to more computational power at your fingertips than the Joint Chiefs of Staff had just 20 years ago. And on top of all that, there’s more capital available to entrepreneurs than ever before. 

Then there’s the major advancements in longevity. 

The cost of things like genome sequencing and stem cell treatments are dropping every year. 

These treatments have massive potential to extend the healthy human lifespan and cure disease...  And it won’t be long until these treatments become affordable to the average person. 

That’s just scratching the surface of some of the major advances that will shape our future. 

And yes. I won’t deny it. Some of the coming disruptive advances in technology are going to create problems in the short term. 

For example, there is no doubt in my mind that artificial intelligence will displace millions of jobs over the coming years, with the potential to create mass technological unemployment. That will be a big problem. 

However, it’s also true that the world’s biggest problems are the world’s biggest business opportunities. 

And as an entrepreneur, you can use these emerging technologies to help solve these problems — and create wealth for yourself — while also making a positive impact on the world. 

But to put yourself in a position to solve these coming problems, you must be able to see them before they happen. 

Leaders anticipate. Followers react. 

Fortunately, you don’t need a crystal ball to see these problems coming. 

There’s a science to accurately predicting what’s coming over the horizon. 

My goal is to show people where the future is going. To show people what technologies are going from deceptive to disruptive. 

And perhaps most importantly of all… To show you how you can take advantage of these coming changes, and massively impact the world, so you are excited about the future, rather than fearful of it. 

Having the right mindset is essential in preparing yourself for these new opportunities. And something I call a “Massively Transformative Purpose,” or MTP. 

I’ve put together free training to teach you exactly what an MTP is, how you can discover your own, and how this knowledge affects everything else you will do for the rest of your life. 

Watch the training video here:
http://getabundance.digital/mtp   

 

If you can anticipate what’s coming, you have a tremendous advantage in life. You don’t want to miss this. 

Best, 

Peter 

7 Types of Companies You Should Never Work For

 @glassdoor "And just say no to places who define “hard work” as 15-hour days and long weekend email threads."

 7 Types of Companies You Should Never Work For

1. The High Turnover Outfit

Red flags: Key roles pop up consistently on a company’s job site.

2. The Culture Clash Corp

Red flags: Negative employee reviews, lack of focus on a true employee experience, recruiters evading your questions.

3. The Curb Appealer

Red flags: Pristine and ideal image in marketing materials and publicity, however, the day-to-day operation is far from glamorous. Only the leaders have what can pass as offices, staff is dispersed amongst shoddy cubicles, lighting is awful, technology is from the ’90s, and let’s not get started on the break room.

4. The Top Heavy Business

Red flags: Too many executives brainstorming, too few employees tasked with executing.

5. The Perpetual Promisor

Red flags: Unfulfilled corporate expectations, employees report a lack of trust in CEO, inability to live up to brand promises.

6. The “Stagnator”

Red flags: Lack of learning opportunities, fails to promote mentorship, offers little more than the role you’ve applied for.

7. The Directionless Ship

Red flags: No clear plan for the future, employees don’t know long-term goals, senior leadership fails to adequately communicate.

The Simple Secret To A High-Performing Team

 How To Build A High-Performing Team
The Simple Secret To A High-Performing Team

1. 1. Build Trust On Your Team

   
   

2. 2. Build Psychological Safety On Your Team

   
   

3. 3. Set Ambitious Goals

   
   

4. 4. Work On Communication Skills

   
   

5. 5. Help Employees Build Confidence

   
   

6. 6. Listen To Your Employees

   
   
   
   
   

Trend driven innovation?

 by @trendwatching … easy

En concreto lo saqué del pdf "The Future of Customer Experience"

Lecciones aprendidas emprendiendo

 por Francisco J. Martín ( @aficionado ) fundador de @bigmlcom

Francisco inició su carrera como becario del MEC en el departamento de Sistemas Informáticos y Computación de la UPV y después en el Instituto de Investigación en Inteligencia Artificial del Consejo Superior de Investigaciones Científicas (CSIC).

En 1999 fundó iSOCO-Intelligent Software Components, uno de los primeros spin-offs del CSIC.

En 2004 participó en Strands que fue vendida a Apple por 49 millones de dólares.

En 2007 fundó BigML.

En el meetup en el que lo escuché hizo un repaso a sus lecciones aprendidas en estos años. Son:

1. Entrena cuerpo y mente, la condición física y mental es esencial
2. Auto-disciplina
3. Equipo y coordinación (pero el "equipo mínimo viable")
4. Permanentemente en economía de guerra
5. Conviértete en un francotirador (focus)
6. Conoce a tus enemigos (competidores, tóxicos dentro)
7. Haz muchos aliados
8. Los planes están para romperlos (Eisenhower)
9. Estar listo para las bajas (cofundadores, empleados…)
10. Desarrolla el sentido del humor

La persona a mi lado, en el cierre de Francisco fue capaz de sintetizar en una frase muy simpática la síntesis de Francisco sobre todo lo que nos habñia contado:

Haz el negocio, no la guerra.

Cuando la carrera cobra más importancia que el destino

~Antoine de Saint-Exupéry; Tierra de los hombres, 1939

"El uso de una herramienta inteligente no te ha convertido en un aburrido técnico. Me parece que esos que tanto se espantan de nuestros progresos confunden el fin con los medios. En efecto, quien siembra con la única esperanza de lograr bienes materiales no logra nada por lo que valga la pena vivir.

La máquina no es un fin.

El avión no es un fin: es una herramienta. Una herramienta como el arado.

Si creemos que la máquina echa a perder al hombre es, tal vez, porque

nos falta un poco de perspectiva para poder emitir un juicio sobre las consecuencias de cambios tan rápidos como los que nos ha tocado vivir.

¿Qué son cien años de historia de la máquina frente a los doscientos mil años de historia del hombre? Acabamos de instalarnos en este paisaje de minas y centrales nucleares. Acabamos de mudarnos a esta nueva casa, que todavía no hemos ni siquiera terminado de edificar. A nuestro alrededor todo ha cambiado muy deprisa: relaciones humanas, condiciones de trabajo, costumbres. Hasta los fundamentos de nuestra psicología se han visto sacudidos. Las palabras separación, ausencia, distancia, regreso, aunque son las mismas, ya no remiten a las mismas realidades. Para aprehender el mundo de hoy usamos un lenguaje creado para el mundo de ayer, y nos parece que la vida del pasado se adecúa mejor a nuestra naturaleza porque responde mejor a nuestro lenguaje.

Cada progreso nos ha alejado un poco mas de unas costumbres que todavía no habíamos tenido tiempo de adquirir,

por lo que somos auténticos emigrantes que aun no han podido fundar su patria.

Todos somos como jóvenes ingenuos que se siguen asombrando frente a juguetes nuevos. Por eso competimos con los aviones: éste sube más alto, ése vuela más rápido. Olvidamos el motivo por el que los hacemos volar. 

La carrera cobra más importancia que el destino,

y siempre ocurre lo mismo. Para el infante del ejército colonizador que funda un imperio, el sentido de la vida es conquistar. El soldado desprecia al colono, pero ¿acaso esa conquista no se lleva a cabo para que el colono pueda afincarse? Del mismo modo, al exaltar nuestros progresos, nos servimos de los hombres para trazar vías férreas, para erigir fábricas, para perforar pozos de petróleo. Casi habíamos olvidado que hacíamos esas obras para que sirvieran a los hombres. Durante la conquista nuestra moral fue una moral de soldados, pero ahora tenemos que colonizar, tenemos que llenar de vida esta casa nueva, que todavía no tiene rostro. La verdad fue, para uno, edificar; la verdad es, para otro, habitar.

Así, poco a poco, nuestra casa se hará más humana. Incluso la máquina, cuanto más se perfecciona, más se difumina detrás de su función. Parece que todo el esfuerzo industrial del hombre, todos sus cálculos, todas las noches en vela encima de los planos, sólo conduzcan de modo visible a la sencillez. Parece que se necesite toda la experiencia de varias generaciones para perfilar lentamente la curva de una columna, de un casco de barco, de un fuselaje de avión, para lograr la pureza primigenia de un seno o de un hombro. Parece que el trabajo de los ingenieros, de los delineantes, de los analistas del centro de estudios, consiste, aparentemente, en borrar y pulir, en aligerar aquel empalme, equilibrar esta ala hasta que ya no se la note, hasta que ya no sea un ala incrustada en un fuselaje, sino una sola forma que, perfectamente lograda, se ha desprendido de su ganga; una forma que sea como un conjunto misteriosamente ensamblado, espontáneo como un poema.

Parece que la perfección se alcanza no ya cuando no queda nada por añadir, sino cuando no queda nada por suprimir. Al término de su evolución, la máquina se disimula.

De esta forma, la perfección del invento reside en la ausencia de invención. Y así como en el instrumento se ha ido borrando cualquier mecánica visible, por lo que disponemos de un objeto tan natural como un guijarro pulido por el mar, el manejo de la máquina, admirablemente, consigue que nos olvidemos de ella.

En otro tiempo teníamos que trabajar con un artefacto complicado. Actualmente nos olvidamos de que un motor gira. A fin de cuentas cumple con su función, la de girar, así como un corazón palpita y no por ello nos fijamos en el nuestro. 

La herramienta ya no absorbe nuestra atención, más allá de sí misma, y gracias a ella encontramos nuestra auténtica naturaleza,

la del jardinero, la del navegante o la del poeta."

The hard part is getting it (the data) organized and figuring out what’s relevant to your process.

Robo-Advisors Aren't A Difficult Tech Problem And Are Already On Their Way To Being Commoditized

Robin: Well, the buzzwords, I’ve noticed, are very much in the financial industry… Is machine learning. But, basically, using more modern artificial intelligence techniques in everything from investing to solving problems that they have on the consumer side, [inaudible 01:01:00]

How much of this is, to return to the cool kids trying to sound with the times, [inaudible 01:01:05] machine learning is very much [inaudible 01:01:07], but do you think, is this a future we’re gonna see more things move that way?

Joe: Yeah. That one, I’m more skeptical of a lot of the efforts I’ve seen in Wall Street. So it might be a little bit more of the cool kids syndrome. I’ve had several CIOs of big institutions ping me saying they have a big machine learning project, and can I connect them to the right people for what they are doing recently.

I mean, machine learning is a tool that all the great technology companies are using now to get done certain things. When you have a bunch of data and you need to figure out what the best answer is, I think you apply it.

I mean, it’s kind of funny, right? It’s artificial intelligence, and once it works we call it machine learning, and there’s all this research on the AI front. I’m definitely bullish on what AI is making possible, but I don’t think it’s this panache or this thing that solves everything. I think the harder problem, frankly, is getting all of your data organized in an infrastructure where you could use it for the problems.

So I think the hard thing to say is, what data should we be using to solve this problem? What is that process? Then once you have all of the data organized, you can hire a single Ph.D. from Stanford. He will do your machine learning thing for you. That’s not that hard. The hard part is getting it organized and figuring out that it’s relevant to this process.

So that’s much more of a strategy and process question to me.

Robin: But you think that it’s gonna be more, I mean, on artificial intelligence. I like that definition, that artificial intelligence is everything we haven’t been able to do that. Everything else is [inaudible 01:02:21]

But how much will we be able to do in the future? I mean, looking forward a little bit.

Joe: Sure.

So I definitely have a few investments in artificial intelligence companies that are trying to push the boundary and change things. I mean, I was actually really surprised that Demis and the team at DeepMind were able to solve the Go problem.

I think that was pretty impressive. But even looking into it, it’s not really capturing, in my view, human creativity, or anything even close to that yet. So I think we’re still decades and decades away from needing to worry about being replaced.

I think the much more interesting problem that we’re focusing on kind of the next 10 or 20 years is, how do we organize the infrastructure of our companies to get the data structured and available to use it for decisions?

I think it’s not gonna be the people who are best at AI and machine learning who win. It’s gonna be the people who are best at that data infrastructure and process problem. I mean, most of the top companies in Silicon Valley, like linear regressions and things, get you 90% of the way. I’m not seeing a lot of really, really hard AI that makes the big difference, for at least the things I’m seeing.

https://youtu.be/_lz2vCOxjOo

From CB Insights – AI & FinTech competition

Sobre la buena vida

Dos entradas para pensar… soy de los toca pelotas de "tenemos suerte".
O de los que dicen que la cosa va bien, que podría ir mejor… pero que podría ir peor y por tanto prefiero no quejarme.

Dos artículos que reflejan mi manera de pensar.


If you’re reading this, you probably don’t do hard work

It may be challenging work. It may be creative work. It may be skilled work. It may require multiple tries to get it right. You may have to learn new things. You may be rejected a bunch. You may get hung up on. You may not know how to get from A to B. You may have to persuade. You may have to deal with people you don’t like. You may have to sell something someone doesn’t know they want. You may have to be creative. You may have to build something that hasn’t been built before. You may have to battle entrenched interests. You may have to put in a few days or weeks in a row to figure something out you’re stuck on. You may have to make tradeoffs. But that’s the work. Not achieving the outcome you wanted doesn’t make it hard, it means you have more work to do.

Stop Pretending You’re Not Rich - NYTimes.com

The rhetoric of “We are the 99 percent” has in fact been dangerously self-serving, allowing people with healthy six-figure incomes to convince themselves that they are somehow in the same economic boat as ordinary Americans, and that it is just the so-called super rich who are to blame for inequality.
“Rather than a poverty trap, there seems instead to be more stickiness at the other end: a ‘wealth trap,’ if you will.”

To Grow Faster, Hit Pause

To Grow Faster, Hit Pause — and Ask These Questions from Stripe’s COO | First Round Review

“A lot of companies don’t decide how they want to grow until they’re well into their growth phase,” she says. “For a long time, your actions pull your company along, and then all of a sudden it switches — your existing business starts pushing your behavior. External forces like feature requests, the need for more customer support, the need to create a team to do X when you never even needed to do X before — those forces start to dictate your decisions.”

The key, she says, is pausing just long enough to be very intentional about how you approach each phase of growth. 

It’s easy to become too reactive, and when that happens, you’ll inevitably start to make human resources mistakes, execution mistakes, prioritization mistakes.

1. Have we documented our operating principles?

Stripe calls them “Operating Principles.” (Many companies have “values,” but Stripe wanted to distinguish philosophical beliefs from the concrete principles that should be applied to the day-to-day work of running the business.) Three of Stripe’s operating principles, as Johnson describes them, are:

• Users first: “We always start with what our users need or would like, and then consider things like like infrastructure, internal constraints, partnerships, product roadmap, and so on."
• Think rigorously: “We care about getting things right and it often takes reasoning from first principles to get there. We work hard to detect the errors in received wisdom. Rigor doesn’t mean not-invented-here syndrome; we’re interested in the world around us and think that other companies, industries, and academic fields have a lot to teach us. But in many cases progress comes from taking paths less traveled.” 
• Trust and amplify: “We want to work in a company of deeply good people who treat their colleagues exceptionally well. People should be committed to amplifying one another: to going out of their way to help each other in both the short- and long-term.”

2. What structure is going to help us achieve our goals?

3. Who has been successful at our company so far?

4. Do we have a 5-year plan?

5. Do we have a way to measure the employee experience?

6. Are we decentralizing decisionmaking?