Quantum computing and new approaches to Artificial Intelligence could get the resources to achieve real breakthroughs in computing

Ramez Naam made a case against a technological Singularity will take longer.

Ramez gives examples and problems to achieving an intelligence explosion
* the complexity of important problems like computational chemistry have exponentially increasing complexity
- if designing intelligence is an N^2 problem, an AI that is 2x as intelligent as the entire team that built it (not just a single human) would be able to design a new AI that is only 70% as intelligent as itself

* There are already entities with vastly greater than human intelligence working on the problem of augmenting their own intelligence. A great many, in fact. We call them corporations. And while we may have a variety of thoughts about them, not one has achieved transcendence.

Let’s focus on as a very particular example: The Intel Corporation. Intel uses the collective brainpower of tens of thousands of humans and probably millions of CPU cores to.. design better CPUs! (And also to create better software for designing CPUs.) Those better CPUs will run the better software to make the better next generation of CPUs. Yet that feedback loop has not led to a hard takeoff scenario.

* should Intel, or Google, or some other organization succeed in building a smarter-than-human AI, it won’t immediately be smarter than the entire set of humans and computers that built it,

Neuromorphic systems that are trying to replicate neurons and synapses and other brain structures are at least one to two decades from achieving the scale of the human mind and then would likely need another decade or three to get the systems to run as well as human minds.

Quantum computers have the technological potential to more rapidly crack larger exponentially complex problems.

Dwave Systems is doubling qubits every year. They are releasing every two years with four times the qubits.

2013      512 qubits
2015     2048 qubits
2017     8192 qubits
2019    64000 qubits
2021   256000 qubits
2023  1 million qubits
2025  4 million qubits
2027 16 million qubits

Dwave could stumble and their systems may prove to not be able to provide sufficient speedup. But there are a few other approaches to quantum computers that could also scale.

Silicon quantum dots

Robert Wolkow and his team reviews their recent efforts in building atom-scale quantum-dot cellular automata circuits on a silicon surface.

* yields of a tiny fraction of 1% have jumped to 80%
* they were producing 100 atomscale quantum dot structures in 1 minute
* In a day with continuous operation 100,000 atomscale quantum dot structures could be built
* they also lay out the case why their dangling bond approach is better than Michelle Simmons’ phosphor atom qubits (it is the 21st century so there are competing atom scale quantum dot and atom scale qubit approaches)

Our building block consists of silicon dangling bond on a H-Si(OO1) surface, which has been shown to act as a quantum dot. First the fabrication, experimental imaging, and charging character of the dangling bond are discussed. We then show how precise assemblies of such dots can be created to form artificial molecules. Such complex structures can be used as systems with custom optical properties, circuit elements for quantum-dot cellular automata, and quantum computing. Considerations on macro—to—atom connections are discussed.

There are proposals for modular trapped ion systems, laser light quantum system, diamond vacancy and these and other approaches would be greatly enhanced with increasing capabilities with molecular nanotechnology. DNA nanotechnology, synthetic biology and improvements to other types of nanoscale control.

More money for potential breakthrough approaches to Artificial Intelligence

There is also more money from Google, Facbook and Venture capital for promising new AI startups. One of the most talked about VC deals in March, for example, was a $40 million round for Vicarious FPC, an artificial intelligence company that had so much hype around it that the biggest names of the tech world – including Mark Zuckerberg and Elon Musk (and Ashton Kutcher) – lined up to participate. And that comes just two months after Google made a monster $400 million bet on DeepMind, an AI start-up based in London. In fact, Google’s Larry Page was so concerned about keeping the DeepMind deal away from Facebook that he took a major role in leading the deal himself.

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