For the past year, as NFTs have breached spectacular and speculative heights, we’ve seen a growing amount of skepticism. The most recent wave was touched off by a 138-minute video essay by Canadian media critic Dan Olson that condemned NFTs and other blockchain-based technologies as fundamentally broken and unworkable. In just over a week, it’s garnered more than 3 million views on YouTube. Regardless of your perspective on the video, it’s hard to deny that there’s a lot of bullshit percolating around NFTs. Even hardcore Bitcoiners agree. And despite what the loudest NFT boosters insist, the beatings have continued and morale has not improved.
Any way you cut it, the NFT ecosystem as it stands is a disaster. Read More
Monthly Archives: February 2022
Don’t forget Microsoft
Despite its scale, Microsoft is one of the most overlooked companies in tech.
- It is not a beloved consumer brand like Apple, Facebook, Amazon, or Google.
- It was not a venture capital success story: Microsoft was too profitable to raise real VC money, so the founders owned 70% at IPO.
- It is the oldest of FAMGA, hidden away in a different state.
This piece undertakes a daunting set of tasks: 1) understand what Microsoft is, 2) chart a path for its global domination, and 3) apply learnings from the company to the startup ecosystem. Read More
#big7
How one company took over the NFT trade
On a cold day in January, NFTs started disappearing. Major services like MetaMask and Twitter were suddenly unable to display images associated with newly uploaded tokens, even though the users had clear records of ownership. Something in the distributed, decentralized technology stack had gone terribly wrong.
The problem was the NFT marketplace OpenSea, which was suffering a database outage. The outage brought down OpenSea’s image-loading API, jamming up any service that relied on it to upload tokens. In a scene full of militant decentralizers, a single company had found its way to the center of nearly every product. Reporting on the chaos, Vice spotted one user who had photoshopped the company’s logo to read “ClosedSea.” Read More
Too Lazy to Write Documentation? Let the AI Write It for You
I’ve never met a developer that enjoys writing documentation. At the very least they understand the value of it and will begrudgingly write it, but will never enjoy the process of writing it.
Some people go by the philosophy that good code should document itself, but if this were true then why is that one person who is familiar with the entire codebase so valuable to a team? There is a lot of knowledge, reasoning, and context that cannot simply be deduced from raw code. Good documentation that’s well-maintained only adds value and context to a codebase.
… AI Doc Writer for Javascript, Typescript, Python, and PHP is a VS Code extension that generates documentation for you using AI. The way it works is that you select the code you want to document and you press the ‘Generate docs’ button or hit the keyboard shortcut Cmd/Ctrl + . Read More
Meet the NSA spies shaping the future
For someone with a deeply scientific job, Gil Herrera has a nearly mystical mandate: Look into the future and then shape it, at the level of strange quantum physics and inextricable math theorems, to the advantage of the United States.
Herrera is the newly minted leader of the National Security Agency’s Research Directorate. The directorate, like the rest of the NSA, has a dual mission: secure American systems and spy on the rest of the world. The budget is classified, a secret among secrets, but the NSA is one of the world’s largest spy agencies by any measure and Herrera’s directorate is the entire US intelligence community’s biggest in-house research and development arm. The directorate must come up with solutions to problems that are not yet real, in a world that doesn’t yet exist.
In his first interview since getting the job, Herrera lays out the tech—and threats—his group will now be focusing on. His priorities show how much the NSA’s targets are changing, balancing its work surveilling terror groups with an appreciation of how rapidly the geopolitical landscape has shifted in recent years. And he explains why the rise of new technologies, in terms of both threat and opportunity, are at the heart of what his group must contend with. Read More
Fake It Till You Make It
We demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone.
The community has long enjoyed the benefits of synthesizing training data with graphics, but the domain gap between real and synthetic data has remained a problem, especially for human faces. Researchers have tried to bridge this gap with data mixing, domain adaptation, and domain-adversarial training, but we show that it is possible to synthesize data with minimal domain gap, so that models trained on synthetic data generalize to real in-the-wild datasets.
We describe how to combine a procedurally-generated parametric 3D face model with a comprehensive library of hand-crafted assets to render training images with unprecedented realism and diversity. We train machine learning systems for face-related tasks such as landmark localization and face parsing, showing that synthetic data can both match real data in accuracy as well as open up new approaches where manual labelling would be impossible. Read More
Dataset
Competitive programming with AlphaCode
Creating solutions to unforeseen problems is second nature in human intelligence – a result of critical thinking informed by experience. The machine learning community has made tremendous progress in generating and understanding textual data, but advances in problem solving remain limited to relatively simple maths and programming problems, or else retrieving and copying existing solutions. As part of DeepMind’s mission to solve intelligence, we created a system called AlphaCode that writes computer programs at a competitive level. AlphaCode achieved an estimated rank within the top 54% of participants in programming competitions by solving new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding.
In our preprint, we detail AlphaCode, which uses transformer-based language models to generate code at an unprecedented scale, and then smartly filters to a small set of promising programs.
We validated our performance using competitions hosted on Codeforces, a popular platform which hosts regular competitions that attract tens of thousands of participants from around the world who come to test their coding skills. We selected for evaluation 10 recent contests, each newer than our training data. AlphaCode placed at about the level of the median competitor, marking the first time an AI code generation system has reached a competitive level of performance in programming competitions.
To help others build on our results, we’re releasing our dataset of competitive programming problems and solutions on GitHub, including extensive tests to ensure the programs that pass these tests are correct — a critical feature current datasets lack. We hope this benchmark will lead to further innovations in problem solving and code generation. Read More
VB Special Issue: The Metaverse: How close are we?
Some elements of the metaverse exist today, but we’re a ways off from seeing its full potential — or even knowing precisely what it is. How will the metaverse evolve in the next few years?
While the metaverse promises to be unlike any technology we’ve seen before and will change the way we work and play, it will both borrow from lessons learned by innovations and paradigm shifts that have gone before it as well as bring us to uncharted tech territories.
In this special report, we look at what we know about the metaverse and the companies driving it, its security risks, what the gaming industry is showing us, how the metaverse could impact the environment, how to ensure it’s open and interoperable. Read More
NFTs in the Uncanny Valley
Non-fungible tokens (NFTs) are so new, weird, and fast that they give even techies future shock. “The street finds its own uses for things,” as William Gibson once wrote. In this case, the blockchain — artists are adopting NFTs today faster than the infrastructure can be built. This delightful inversion of the normal product/market fit challenge puts them in an “uncanny valley.” NFTs are a new form of digital object, and we have yet to see what they are capable of.
Famed multimedia artist Brian Eno asks a great question about NFTs in an interview with Evgeny Morozov in the Crypto Syllabus:
“I want to know what is changing, what is being made different, what is helping, what is moving?”
We need more people like Eno in the conversation. The teams building NFT technology are motivated by the public good and hungry for input from thoughtful critics. The current speculative environment sometimes feels like a distraction from the long-term potential of what we are building, but at the same time, this spike of awareness is a golden opportunity to invite new voices to help clarify the vision and purpose of what we are building.
Eno’s questions are a lens focused on the cultural value of NFTs. Let’s take them one at a time: Read More
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