Skip to main content

Startup malaise, startup ambition

Recapped. Layoffs. Slowdown. CEO transition. Budget cuts. Downsizing.

In spite of a spate of massive startup exits the last few months, culminating in fintech’s shining moment yesterday with Intuit’s $7.1 billion acquisition of Credit Karma, it’s been a tough period for the startup world. Layoffs abound, centered perhaps on SoftBank’s Vision Fund portfolio but hardly exclusive to it. Startups, both infamous and unheard of, are shutting their doors. And that doesn’t even begin to factor in the global macro concerns like coronavirus that will drive investor sentiment this year.

There’s a bit of malaise underway in the startup world, a sense that possibilities are closing, that everything that will be built has been built, that tech itself is under an excruciating microscope by the public that makes innovation impossible.

All of that may well be true. And yet, there remains so, so much more to get done.

Whole sectors of the economy still need to be completely rebuilt from the ground up. Healthcare is barely digital, never personalized and based on almost no evidence or data whatsoever. Construction costs for housing and infrastructure have skyrocketed, with almost no real benefit to the end user whatsoever. Millions of people are facing student debt crises, and yet our school system doesn’t look all that much different from a century ago.

Climate change itself is going to eat away at more and more of the planet, just as several billion more people come online, join the industrial and knowledge economies and demand the same amenities offered in the developed world. How do we offer air conditioning, housing, transportation, healthcare and more to every human on the planet? We need to 100x the global GDP while cutting carbon emissions, and billions of people are counting on us.

Within organizations, we are still just beginning to figure out how design, data and decisions work together to drive product innovation and growth. I just wrote about a prototyping tool yesterday, following up on my colleague Jordan Crook’s look at what has been happening in the design world. Yes, the tools are getting better, but what would happen if a million more people could effortlessly design? Or what would happen if billions of people had access to no-code platforms more broadly? What could we empower them to create?

Or just take our general experience with digital products. Our phones are faster, the photos they take are at exquisite resolutions and their svelte materiality remains superb. But do they really offer a seamless experience? I am still syncing files, tracking emails, attempting to connect a lunch meeting to my calendar and not dropping the details while flicking my fingers back and forth. The mundane nature of our daily software usage belies the reality that we use ridiculously elementary tools compared to what is possible even with today’s technology, no hand waving required.

And then there is data. The data revolution in business, entertainment, government and more is barely in its infancy. Data may be slushing around large enterprises, but it hardly makes a dent on decision-making, even today. What would happen if we could use data more effectively? What if we could explore data even faster than today’s clunky BI tools? What if the best patterns for exploring data were readily available to every single person on Earth? What if we could instantly and easily build best-of-breed AI models to solve even our simplest decision-making problems?

I could go on for pages and pages. From specific markets, to the dynamics within communities, and societies and companies, to the end users and the products they are offered, we are nowhere near the end of the innovation cycle. This isn’t Detroit circa a century ago, when hundreds of auto manufacturers and related companies eventually combined into a handful of today’s behemoths. There is still so much to do, and FAANG can’t do it all.

What’s crazy is that within the right circles, there has never been a wider sense of awe at the gap between what we know to do and what we know we need to do. There are so many unsolved challenges today worth exploring that could not only help the lives of tens of millions of people, but that could also be multi-billion-dollar economies themselves.

And so we need to bifurcate our sentiments. We do need to memorialize the failed startups, the ambitions that never quite made it. We need to recognize when mistakes are made, and have empathy for those affected by them. We shouldn’t ignore the negative news of our industry at all, lest we repeat the same blunders.

Yet, a positive sentiment in the face of this avalanche of negative news and critical analysis is vital. You have to keep your eye on the future, on the change, on the power that still rests with all of us to make a difference right now. So much needs to be done, and the day is still young.



from TechCrunch https://ift.tt/2w2ZtqL
via IFTTT

Comments

Popular posts from this blog

Apple’s AI Push: Everything We Know About Apple Intelligence So Far

Apple’s WWDC 2025 confirmed what many suspected: Apple is finally making a serious leap into artificial intelligence. Dubbed “Apple Intelligence,” the suite of AI-powered tools, enhancements, and integrations marks the company’s biggest software evolution in a decade. But unlike competitors racing to plug AI into everything, Apple is taking a slower, more deliberate approach — one rooted in privacy, on-device processing, and ecosystem synergy. If you’re wondering what Apple Intelligence actually is, how it works, and what it means for your iPhone, iPad, or Mac, you’re in the right place. This article breaks it all down.   What Is Apple Intelligence? Let’s get the terminology clear first. Apple Intelligence isn’t a product — it’s a platform. It’s not just a chatbot. It’s a system-wide integration of generative AI, machine learning, and personal context awareness, embedded across Apple’s OS platforms. Think of it as a foundational AI layer stitched into iOS 18, iPadOS 18, and m...

The Silent Revolution of On-Device AI: Why the Cloud Is No Longer King

Introduction For years, artificial intelligence has meant one thing: the cloud. Whether you’re asking ChatGPT a question, editing a photo with AI tools, or getting recommendations on Netflix — those decisions happen on distant servers, not your device. But that’s changing. Thanks to major advances in silicon, model compression, and memory architecture, AI is quietly migrating from giant data centres to the palm of your hand. Your phone, your laptop, your smartwatch — all are becoming AI engines in their own right. It’s a shift that redefines not just how AI works, but who controls it, how private it is, and what it can do for you. This article explores the rise of on-device AI — how it works, why it matters, and why the cloud’s days as the centre of the AI universe might be numbered. What Is On-Device AI? On-device AI refers to machine learning models that run locally on your smartphone, tablet, laptop, or edge device — without needing constant access to the cloud. In practi...

Max Q: Psyche(d)

In this issue: SpaceX launches NASA asteroid mission, news from Relativity Space and more. © 2023 TechCrunch. All rights reserved. For personal use only. from TechCrunch https://ift.tt/h6Kjrde via IFTTT