* Bitcoin number of transactions (excluding popular addresses):
* Bitcoin number of unique addresses used:
Bitcoin price continues to bounce with another USMS auction coming up soon. As time winds down $817 by this Christmas seems increasingly unlikely supporting the idea that on price, this is just a lost year for Bitcoin. Of course a lost year in price growth is a chance to build infrastructure for the next climb. – Bingo Boingo
Blockstream’s $21 million in Funding
Blockstream aims to enhance bitcoin’s “blockchain” — the distributed, public ledger that is the defining technological feature — and turn it into a universal platform for multiple new applications that go far beyond the digital-currency payments for which bitcoin is best known.
Blockstream has no clear roadmap on how it will turn an open-source software engineering project into a corporate money-maker. Instead, investors took a leap of faith, mostly based on the reputations of the company’s co-founders, who Tally Capital partner and co-contributor Matthew Roszak described as the “highest caliber of human capital in the blockchain planet.”
Still, the indeterminate nature of Blockstream’s business model made it a complicated investment for many venture capitalists, who typically must justify returns to their investors. The manager of one fund said he turned down the pitch because he couldn’t invest in such a vague plan. Mr. Hoffman said he invested via his personal not-for-profit foundation, not his Greylock Partners firm, because he felt strongly that Blockstream’s first funding round “had to be invested in the development of the bitcoin ecosystem and not have, as its primary focus, economic returns – Michael J. Casey
Pierre Rochard: Ethereum will have to overcome Bitcoin’s liquidity advantage, take on risks of a rewrite from scratch, and implement complex features. The first challenges economic law, the second two are Herculean feats of software engineering. God speed.
Oh and they have to do it all before their theoretical competitive advantages are eroded by incumbents and challengers –
Jimmy Song: Don’t forget all the coin cloners that have access to the same open source code
Pierre Rochard: yes, that makes their pre-sale especially amazing
Price Discovery Mechanism
My view is the Fed has made a mockery of fundamentals, that there is no real natural price discovery. It’s leading toward malinvestment. – Doug Kass
COMPANIES / PROJECTS
How Seasteading can improve the world – Mammoth Infographics
Kevin Carson: The real problem is not that Uber is competing with medallion cab companies, but that open-source competition hasn’t yet destroyed Uber.
JJ: We have some ideas but we’re stretched and infrastructure is limited. But it’ll happen.
Michael Goldstein: You’ll never be able to scam VCs with that attitude. More block chain tech! More mixed metaphors! More faux-humanitarianism!
Around 2002 I attended a small party for Google—before its IPO, when it only focused on search. I struck up a conversation with Larry Page, Google’s brilliant cofounder, who became the company’s CEO in 2011. “Larry, I still don’t get it. There are so many search companies. Web search, for free? Where does that get you?”
My unimaginative blindness is solid evidence that predicting is hard, especially about the future, but in my defense this was before Google had ramped up its ad-auction scheme to generate real income, long before YouTube or any other major acquisitions. I was not the only avid user of its search site who thought it would not last long. But Page’s reply has always stuck with me: “Oh, we’re really making an AI.”
I’ve thought a lot about that conversation over the past few years as Google has bought 14 AI and robotics companies. At first glance, you might think that Google is beefing up its AI portfolio to improve its search capabilities, since search contributes 80 percent of its revenue. But I think that’s backward. Rather than use AI to make its search better, Google is using search to make its AI better. Every time you type a query, click on a search-generated link, or create a link on the web, you are training the Google AI.
When you type “Easter Bunny” into the image search bar and then click on the most Easter Bunny-looking image, you are teaching the AI what an Easter bunny looks like. Each of the 12.1 billion queries that Google’s 1.2 billion searchers conduct each day tutor the deep-learning AI over and over again. With another 10 years of steady improvements to its AI algorithms, plus a thousand-fold more data and 100 times more computing resources, Google will have an unrivaled AI. My prediction: By 2024, Google’s main product will not be search but AI – Kevin Kelly
Anonymity in p2p Markets
To achieve real anonymity when chatting with strangers (e.g. blackmarket merchants), one needs to use a combination of these factors:
1) Bitmessage or alike to avoid evesdropping.
2) Tor to make it harder for recipient to find location of the sender.
3) Low-latency network to make statistical analysis less efficient. Every relaying node (both Tor and Bitmessage) should delay broadcasting messages randomly.
4) Infrequent communication, so it takes time for recipient to gather data. (This is a variant of #3)
5) Change physical location frequently, randomly and rarely reuse them. E.g. connect from various free wi-fi points in cafes, parks, shops, Apple Stores etc.
6) Never reuse identity between people you communicate with. Merchants must have separate Bitmessage and Bitcoin address per invoice (once item is sold, post another item with different identity). Buyers must use different Bitmessage and Bitcoin address for each purchase. This way amount of information available to an adversary will be strictly limited to just one deal. And that deal will be limited to one unique location and a few exchanged messages that hopefully won’t be enough to locate the person. And even if that happens, person couldn’t be charged with more than one sin.
If you communicate with people you trust (friends, family members), you only need #1 and that would be enough.
The chart and data tell a powerful and remarkable story of job creation in the Lone Star State of more than 1.36 million new jobs added since the start of the Great Recession, compared to a net deficit of 354,000 jobs for the other 49 states combined.
Much of the economic success of Texas in recent years that has fueled job creation in the state is a direct result of the shale oil and gas boom taking place in areas like the Permian Basin in west Texas (1.8 million barrels of oil per day) and the Eagle Ford in south central Texas (1.6 million barrels per day). Texas is now producing almost 37% of America’s total crude oil production, and as a separate country would be the world’s 8th largest oil-producer.
Further, Texas has done a great job of attracting businesses like Toyota because of the state’s “employer-friendly combination of low taxes, fair courts, smart regulations and world-class workforce.” – Mark J. Perry
An exponential trend seems unimportant until it is all important – Balaji S. Srinivasan
Tech’s Pace is Like a Dozen Gutenberg Moments Happening at the Same Time
Drilling down into the concepts and consequences of our exponential pace, Singularity University’s global ambassador and founding executive director, Salim Ismail, set the stage.
We’re at an inflection point, he said, where we are digitizing and augmenting the human experience with technology. That digitization is accelerating change. The question is: How can individuals and society, more generally, navigate it?
Five hundred years ago, Johannes Gutenberg’s printing press freed information as never before. Ismail framed the current pace of technology as Gutenberg to the extreme, “We’re having about a dozen Gutenberg moments all at the same time.”
Ismail showed a video of someone riding in one of Google’s self-driving cars as it navigated an obstacle course at top speed. The rider is amazed and a little nervous—the video ends with him letting out a little involuntary scream. Today, the world is letting out a little collective Google scream. – Jason Dorrier
The Business Plans of the Next 10,000 Startups Are Easy to Forecast: Take X and Add AI
A picture of our AI future is coming into view, and it is not the HAL 9000—a discrete machine animated by a charismatic (yet potentially homicidal) humanlike consciousness—or a Singularitan rapture of superintelligence. The AI on the horizon looks more like Amazon Web Services—cheap, reliable, industrial-grade digital smartness running behind everything, and almost invisible except when it blinks off.
This common utility will serve you as much IQ as you want but no more than you need. Like all utilities, AI will be supremely boring, even as it transforms the Internet, the global economy, and civilization. It will enliven inert objects, much as electricity did more than a century ago. Everything that we formerly electrified we will now cognitize.
This new utilitarian AI will also augment us individually as people (deepening our memory, speeding our recognition) and collectively as a species. There is almost nothing we can think of that cannot be made new, different, or interesting by infusing it with some extra IQ. In fact, the business plans of the next 10,000 startups are easy to forecast: Take X and add AI. This is a big deal, and now it’s here. – Kevin Kelly
The Virtual Reality Era
This is it. The peak of the pre-VR computing era. Enjoy. – Chris Dixon, Andreessen Horowitz
Follow me on Twitter @leebanfield1