1. There’s no practical technology currently available to scan a large brain with sufficient detail. This problem is discussed in “WBE: A Roadmap” (Ref 6). It’s not at all clear when such technology will become available.

2. We don’t know what level of detail will be “sufficient” to emulate a brain. It’s likely that a very high resolution scanning will be necessary, given the “Blind Replication” goal. When you don’t understand something, you need to copy more detail. This makes 1. even harder to achieve.

3. Even when the technology for 1. and 2. appears, it will allow scanning of a dead brain tissue. This means we will be able to replicate a “dead brain”. Obviously, dead brains are not very intelligent, and it’s not at all clear how to bring a dead brain to life (biological or not), especially if the copy isn’t perfect (and it will be pretty hard to make a “perfect copy”).

4. To address the concern in 3. it might be possible to replicate a simpler brain structure that can potentially be grown into a brain (like an embrio brain), and then given opportunity to learn like a human child does.

5. Signal speed does not equate to processing speed. This is especially true when you are blindly replicating something designed to work at slow speeds. Therefore there’s no reason to assume an emulated brain will work any faster than a human brain.
This means a learning stage mentioned in 4. will likely take comparable amount of time it takes a human brain to learn (years). As any circuit designer will tell you, it’s hard to speed something up when you don’t understand how it works (and often it’s hard even when you do).

6. Even if the above problems are solved, the resulting intelligence will be something resembling a human being, nothing less, nothing more. What makes you think this being will want to do anything? What makes you think you can force it to do anything? It’s really hard to imagine its motivations, or values. It’s not clear if it will have any.
Perhaps if you give it a physical body — a human-like body with human-like senses, then maybe it will do something, but still, its behavior is likely to be very different from a behavior of a healthy person.

7. The central idea of the article — WBE + AGI is easier than AGI.

Let’s look at the current status of both fields: in AGI, probably the most impressive achievement to date is IBM Watson. It was able to “understand” sophisticated (but very specific) questions, and answer them correctly given access to relevant information.
With all its limitations, Watson is a pretty impressive piece of technology. It’s not hard to see the future where Watson will grow into something that can do much more, given more processing power, new/better algorithms, and access to more data.

WBE progress, on the other hand, can be evaluated by looking at Blue Brain Project (the core of the future Human Brain Project). They showed a simulation of about 100 cortical columns. It’s not entirely clear how well those columns are simulated, because no functional virtual organism has ever been demonstrated. As another commenter here noted, not even the smallest brain has ever been simulated (C Elegans worm has only ~300 fully mapped neurons, yet no one has been able to emulate it so far. David Dalrymple is currently working on it, and he claims to be able to do it in the nearest future — we’ll see).

Bottom line — so far it seems AGI has been more successful compared to WBE. Of course, this may change in the future (especially given the amount of funding promised for the HBP), but I don’t see any arguments in the article to support the claim that WBE is “easier” than AGI.