1 Bitcoin = $413
Bullish Case for Bitcoin
- Negative interest rates
- Efforts to ban cash
- Mobile growth
- Capital controls
- Currency wars
I couldn’t dream of more bullish case for bitcoin. – Barry Silbert
“Bitcoin” vs. “Bitcoins”
Noob interest in acquiring Bitcoin is exploding …
Bitcoin ecosystem suffering from cabin fever: https://en.wikipedia.org/wiki/Cabin_fever
Everyone should go on a vacation, learn a new skill, meditate, etc. – Pierre Rochard
Bitcoin Dominance Index
Bitcoin Dominance Index falls to 76% – CoinCap
Ethereum Over $1 billion
A rise of 1550% in 100 days: Coinmarketcap.com/ethereum
ShapeShift Volumes Surge as Demand for Ethereum Explodes
ShapeShift grew 1,000% in 2015. It has already grown another 1,000% in the first 2 months of 2016. Thank you everyone! #Bitcoin #Ethereum – Erik Voorhees
PRIVACY / SECURITY / INTERNET
Private bitcoin transactions, via decentralized mixing, for low fees: github.com/JoinMarket
Money was never meant to be a government tracking mechanism. – Jon Matonis
L.A. Hospital Pays $17K Ransom in Bitcoin to Regain Control of Hacked Computers
If bitcoin is traceable, then why is it used in these types of transactions?
None of the hacked stolen btc from Gox or Bitstamp have ever been located. #forensics – Jon Matonis
Top 5 Wallets of 2016 for Privacy
The Open Bitcoin Privacy Project (OBPP) released its 2nd edition review of the “Bitcoin Wallet Privacy Rating Report.”
The creators say the wallet review is a way to “measure their effectiveness at protecting user privacy.”
The number one Bitcoin wallet on the list this year goes to the hardware device Ledger Wallet.
The group says, “we found it outperformed its competitors in handling privacy basics.” This includes avoiding address reuse, and support for multiple accounts within a single wallet.
Number two on the list is BreadWallet
Airbitz takes the third position in the privacy report with its hierarchical deterministic (HD) wallet
Darkwallet was the OBPP’s top contender last year but has now dropped to the fourth position. Lack of development has left Darkwallet’s code collecting dust and the organization says it’s remained “untouched since our last review.” This, in turn, threatens the model with progress by the many competitors coming into the wallet ecosystem. However, the project still holds a couple features others have not yet accomplished. OBPP explains in the report:
To date, Darkwallet is still one of only two graphical wallets with CoinJoin support, and one of a handful with ECDHM address support. Darkwallet enables both CoinJoin and ECDHM addresses by default. However, disuse has reduced the available number of Darkwallet partners for CoinJoin transactions, yielding very limited use at present. After a short timeout period, if no other users are available to mix with, the transaction will proceed without the use of CoinJoin.
5G Could be Done Long Before 2020
5G is coming faster than most people think, Nokia CEO Rajeev Suri says.
The next generation of mobile networks will start to get defined “in real terms” by the end of this year, Suri said at a press briefing.
Official estimates say the 5G standard won’t be complete until 2020. Suri thinks there’s too much demand to wait that long.
“2020 is probably when we’ll see global volume deployments, but we’ll probably start to see a lot of action, in an evolutionary way, ahead of 2020—2017, 2018, 2019,” he said.
Users and service providers know more about what they need 5G for, at this stage of the game, than they did when 3G and 4G were being developed, Suri said.
Key needs include high speed for video and virtual reality, low latency for vehicle-to-vehicle communication, and the ability to connect thousands of devices to a cell. – Stephen Lawson
Investing in Robotics and AI Companies
Here are some AI (and robotics) related companies to think about.
I’m not saying you should buy them (now) or sell for that matter, but they are definitely worth considering at the right valuations.
Think about becoming an owner of AI and robotics companies while there is still time. I plan to buy some of the most obvious ones (including Google) in the ongoing market downturn (2016-2017).
Top 5 most obvious AI companies
- Alphabet (Google)
- Facebook (M, Deep Learning)
- IBM (Watson, neuromorphic chips)
- Apple (Siri)
- MSFT (skype RT lang, emo)
- Amazon (customer prediction; link to old article)
Yes, I’m US centric. So sue me 🙂
- SAP (BI)
- Oracle (BI)
- Nuance (HHMM, speech)
- Nippon Ceramic
- Pacific Industrial
Private companies (*I think):
- *Scaled Inference
- *Expect Labs
- *Nara Logics
- *Context Relevant
- *Rethink Robotics
- *Sentient Technologies
General AI areas to consider when searching for AI companies
- Self-driving cars
- Language processing
- Search agents
- Image processing
- Machine learning
- Oil and mineral exploration
- Pharmaceutical research
- Materials research
- Computer chips (neuromorphic, memristors)
- Energy, power utilities
COMPANIES / PROJECTS / PRODUCTS
Mind blown today at TED imagining a future where you walk around the moon with Neil Armstrong w/Hololens. – Bill Gross
Compared to Oculus Rift and Gear VR, Microsoft HoloLens offers an authentic augmented-reality experience, meaning the images coming from the device are projected on the user’s actual environment.
The device is doing it by projecting light directly to the user’s eyes to draw images.
The HoloLens Development Edition pre-orders started on Feb. 29.
The much-awaited virtual reality (VR) headset from Microsoft costs $3,000 and its shipping starts at the end of March.
The consumer edition of the device is expected to be released very soon. – Mark Aserit
DJI’s Phantom 4 Drone
Revolutionary drone can dodge obstacles and track humans.
Computer vision software allows the Phantom 4 to fly autonomously.
The new Phantom isn’t cheaper than previous versions: in fact at $1,399, it’s more expensive than the top-tier Phantom 3 was at release. But the pitch from DJI to consumers, especially beginners, is different this time.
With the new suite of autonomous features you are way less likely to wreck your aircraft, and you don’t need to spend any time mastering manual piloting to capture great aerial footage.
On March 15th it will be available in-store at DJI’s flagship store in Shenzhen, and as the first drone prominently featured in Apple Stores around the world. – Ben Popper
Solar PV Installations Surging
DeepMind Smartphone Assistant
The movie Her is just an easy popular mainstream view of what that sort of thing is. We would like these smartphone assistant things to actually be smart and contextual and have a deeper understanding of what you’re trying to do.
At the moment most of these systems are extremely brittle — once you go off the templates that have been pre-programmed then they’re pretty useless. So it’s about making that actually adaptable and flexible and more robust.
It’s this dichotomy between pre-programmed and learnt. At the moment pretty much all smartphone assistants are special-cased and pre-programmed and that means they’re brittle because they can only do the things they were pre-programmed for. And the real world’s very messy and complicated and users do all sorts of unpredictable things that you can’t know ahead of time.
Our belief at DeepMind, certainly this was the founding principle, is that the only way to do intelligence is to do learning from the ground up and be general.
I think in the next two to three years you’ll start seeing it. I mean, it’ll be quite subtle to begin with, certain aspects will just work better. Maybe looking four to five, five-plus years away you’ll start seeing a big step change in capabilities. – Demis Hassabis
Google’s Boston Dynamics Has Created the Most Human Robot Yet
Boston Dynamics just released another incredible video featuring its latest version of the humanoid robot, ATLAS that was initially developed for the DARPA Robotics Challenge.
The company says this version is the “next generation” of their humanoid, but the technological leap they have made is far from incremental.
This incredibly upgraded model of ATLAS is electrically powered and hydraulically actuated. It uses sensors in its body and legs to balance and LIDAR and stereo sensors in its head to avoid obstacles, assess the terrain, help with navigation and manipulate objects.
Seriously, the gulf between the robots featured in contemporary science fiction like Chappie and the stuff coming out of Boston Dynamics does not seem that far apart anymore. It is amazing how far the robot has been developed in the past three years! – 33rd Square
Google’s AI Takes Historic Match Against Go Champ
* Machines have conquered the last games. Now comes the real world
Google’s artificially intelligent Go-playing computer system has claimed victory in its historic match with Korean grandmaster Lee Sedol after winning a third straight game in this best-of-five series.
Go is exponentially more complex than chess and requires an added level of intuition—at least among humans. This makes the win a major milestone for AI—a moment whose meaning extends well beyond a single game.
Just two years ago, most experts believed that another decade would pass before a machine could claim this prize. But then researchers at DeepMind—a London AI lab acquired by Google—changed the equation using two increasingly powerful forms of machine learning, technologies that allow machines to learn largely on their own. Lee Sedol is widely regarded as the best Go player of the past decade. But he was beaten by a machine that taught itself to play the ancient game..
The machine learning techniques at the heart of AlphaGo already drive so many services inside the Internet giant—helping to identify faces in photos, recognize commands spoken into smartphones, choose Internet search results, and much more. They could also potentially reinvent everything from scientific research to robotics
The machine plays like no human ever would—quite literally.
Using what are called deep neural networks—vast networks of hardware and software that mimic the web of neurons in the human brain—AlphaGo initially learned the game by analyzing thousands of moves from real live Go grandmasters. But then, using a sister technology called reinforcement learning, it reached a new level by playing game after game against itself, coming to recognize moves that give it the highest probability of winning.
The result is a machine that often makes the most inhuman of moves.
This happened in Game Two—in a very big way. With its 19th move, AlphaGo made a play that shocked just about everyone, including both the commentators and Lee Sedol, who needed nearly fifteen minutes to choose a response. The commentators couldn’t even begin to evaluate AlphaGo’s move, but it proved effective. Three hours later, AlphaGo had won the match.
This week’s match is so meaningful because this ancient pastime is so complex. As Google likes to say of Go: there are more possible positions on the board than atoms in a universe.
Just a few days earlier, most in the Go community were sure this wasn’t possible. But these wins were decisive. Machines have conquered the last games. Now comes the real world. – Cade Metz
DeepMind Founder Demis Hassabis Wants to Solve Intelligence
The aim of DeepMind is not just to beat games, fun and exciting though that is. It’s to the extent that they’re useful as a testbed, a platform for trying to write our algorithmic ideas and testing out how far they scale and how well they do and it’s just a very efficient way of doing that. Ultimately we want to apply this to big real-world problems.
We’re concentrating on the moment on things like healthcare and recommendation systems, these kinds of things.
What I’m really excited to use this kind of AI for is science, and advancing that faster. I’d like to see AI-assisted science where you have effectively AI research assistants that do a lot of the drudgery work and surface interesting articles, find structure in vast amounts of data, and then surface that to the human experts and scientists who can make quicker breakthroughs.
I was giving a talk at CERN a few months ago; obviously they create more data than pretty much anyone on the planet, and for all we know there could be new particles sitting on their massive hard drives somewhere and no-one’s got around to analyzing that because there’s just so much data. So I think it’d be cool if one day an AI was involved in finding a new particle. – Demis Hassabis
Does Google Deepmind’s A.I. Exhibit Super-Human Abilities? Some Japanese Pros Think So:
The Power and the Mystery
At first, Fan Hui thought the move was rather odd. But then he saw its beauty.
“It’s not a human move. I’ve never seen a human play this move,” he says. “So beautiful.” It’s a word he keeps repeating. Beautiful. Beautiful. Beautiful.
The move in question was the 37th in the second game of the historic Go match between Lee Sedol, one of the world’s top players, and AlphaGo, an artificially intelligent computing system built by researchers at Google. Inside the towering Four Seasons hotel in downtown Seoul, the game was approaching the end of its first hour when AlphaGo instructed its human assistant to place a black stone in a largely open area on the right-hand side of the 19-by-19 grid that defines this ancient game. And just about everyone was shocked.
“That’s a very strange move,” said one of the match’s English language commentators, who is himself a very talented Go player. Then the other chuckled and said: “I thought it was a mistake.” But perhaps no one was more surprised than Lee Sedol, who stood up and left the match room. “He had to go wash his face or something—just to recover,” said the first commentator.
Even after Lee Sedol returned to the table, he didn’t quite know what to do, spending nearly 15 minutes considering his next play. AlphaGo’s move didn’t seem to connect with what had come before. In essence, the machine was abandoning a group of stones on the lower half of the board to make a play in a different area.
AlphaGo placed its black stone just beneath a single white stone played earlier by Lee Sedol, and though the move may have made sense in another situation, it was completely unexpected in that particular place at that particular time—a surprise all the more remarkable when you consider that people have been playing Go for more than 2,500 years.
The commentators couldn’t even begin to evaluate the merits of the move. – Cade Metz
* Now imagine the same ultra-competency being developed in other endeavors like medicine, law, scientific research, and war. – Veteran4Peace
AI Can Put Us on the Most Optimal Paths to Solving Problems
Just like this game of Go, AI will eventually start ‘thinking in ways we never conceived’ about many things like curing diseases.
There could be 50 different promising paths to curing cancer for instance but only enough funding and scientists to tackle the first 5 we think of, even if the ultimate cure is on one of the other 45.
What a fascinating idea it is that perhaps AI will think of every path and always put us on the most optimal ones. – iushciuweiush
What Problems Can Humans and Machines Overcome Together?
The AI research community has made incredible progress in five years.
A key insight has been that it’s much better to let computers figure out how to accomplish goals and improve through experience, rather than handcrafting instructions for every individual task. That’s also the secret to AlphaGo’s success.
The real challenges in the world are not “human versus machine,” but humans and whatever tools we can muster versus the intractable and complex problems that surround us. The most important struggles already have thousands of brilliant and dedicated people making progress on issues that affect every one of us.
Technologies such as AI will enhance our ability to respond to these pressing global challenges by providing powerful tools to aid experts make faster breakthroughs. We need machine learning to help us tame complexity, predict the unpredictable and support us as we achieve the previously impossible.
As our tools get smarter and more versatile, it’s incumbent upon us to start thinking much more ambitiously and creatively about solutions to society’s toughest global challenges. We need to reject the notion that some problems are just intractable. We can aim higher.
Consider what the world’s best clinicians or educators could achieve with machine learning tools assisting them. The real test isn’t whether a machine can defeat a human, but what problems humans and machines can overcome together. – Sundar Pichai and Demis Hassabis
AI is Coming
Artificial Intelligence keeps progressing, no matter whether you know about (or like it) or not.
First an AI application is typically seen as a curiosity. Then it becomes a tool you need to learn how to use. And eventually it will develop to the point where it could take your job.
IBM’s Watson easily beat the world’s best Jeopardy masters several years ago. Since then it has become the world’s foremost oncology expert.
Currently Watson is on its way to start replacing swathes of paralegals at law firms as well as finding new oil reserves.
A few years down the road, anyone with a cellphone (or AugReal contact lens) will be able to tap into Watson-like powers for any kind of search or research. – Mikael Syding
Anticipated Top AI Breakthroughs: 2016 – 2018
At A360 this year, my expert on AI was Stephen Gold, the CMO and VP of Business Development and Partner Programs at IBM Watson.
AI Progress of late is furious — an R&D arms race is underway among the world’s top technology giants.
Soon AI will become the most important human collaboration tool ever created, amplifying our abilities and providing a simple user interface to all exponential technologies. Ultimately, it’s helping us speed toward a world of abundance.
The implications of true AI are staggering,
“It’s amazing,” said Gold. “For 50 years, we’ve ideated about this idea of artificial intelligence. But it’s only been in the last few years that we’ve seen a fundamental transformation in this technology.”
Here are Gold’s predictions for the most exciting, disruptive developments coming in AI in the next three years. As entrepreneurs and investors, these are the areas you should be focusing on, as the business opportunities are tremendous.
1 – Next-gen A.I. systems will beat the Turing Test
Alan Turing created the Turing Test over half a century ago as a way to determine a machine’s ability to exhibit intelligent behavior indistinguishable from that of a human.
Loosely, if an artificial system passed the Turing Test, it could be considered “AI.”
Gold believes, “that for all practical purposes, these systems will pass the Turing Test” in the next three-year period.
Perhaps more importantly, if it does, this event will accelerate the conversation about the proper use of these technologies and their applications.
2 – Leverage ALL health data (genomic, phenotypic, social) to redefine the practice of medicine.
“I think AI’s effect on healthcare will be far more pervasive and far quicker than anyone anticipates,” says Gold. “Even today, AI/machine learning is being used in oncology to identify optimal treatment patterns.”
But it goes far beyond this. AI is being used to match clinical trials with patients, drive robotic surgeons, read radiological findings and analyze genomic sequences.
3 – AI will be woven into the very fabric of our lives — physically and virtually.
Ultimately, during the AI revolution taking place in the next three years, AIs will be integrated into everything around us, combining sensors and networks and making all systems “smart.”
AIs will push forward the ideas of transparency, of seamless interaction with devices and information, making everything personalized and easy to use. We’ll be able to harness that sensor data and put it into an actionable form, at the moment when we need to make a decision.
Follow me on Twitter @leebanfield1