How to manage “AI” development and R&D team in big corporations without “casting spells” and “doing rain dances”?

As my main work is related to AI and brains for robots, ( and I write in a blog about AI use cases in different industries, some big corporations involved in traditional industries ask me to help them solve problems with their AI research & development.

Usually, these problems are related to “over-budgeting” of R&D or issues with goal setting, or inefficient management in R&D teams.

Here are the most common issues and takeaways from my experience:

#1. “AI” is not magic and should be developed and delivered within time limits and budgets.

Almost all tasks (roughly 90%) performed in areas of Computer Vision and Machine Learning are not related to “real” R&D (creating algorithms or significant improvements).
For a successful implementation, it is usually enough to find a relevant, previously published paper and implement it well.
So there is no need to call “shamans” who will cast the spell and tell you about the “magic” of AI, but who won’t tell you when and how the problem can be solved. Hire only those specialists who can in a highly technical way describe the entire process involved in reaching the goal and who do not start reinventing the wheel instead of implementing a popular correct method.

#2. For the hardest R&D tasks in “AI” people are your primary asset, for other tasks rely on data.

When working on standard functions, you can hire average professionals, whose task will most likely be to create a well-marked and cheap dataset, implement a properly defined approach and build a system for correct data collection and subsequent algorithmic training. In this case, datasets and data itself, which was created and collected in the process of using the system (i.e., through its additional training, etc.) are the main assets of the business.

If the development accounts for 10% of your tasks and its implementation requires serious R&D, then your main asset is the people who implement the solution. Therefore, the majority of your and your competitors’ budgets will be spent not on implementation, but testing hypotheses. In this case, it is essential to know precisely which paths lead to results, and which paths do not.

Of course, when creating such projects, you need to reinforce your competitive advantage with an efficient logging system, data collection system, and a subsequent training system.

#3. The hardest part is the integrating of AI solutions into business processes. Developing a solution is the easiest part.

If a large corporation creates a well-functioning AI solution, they will soon be surprised to find out that the integration of the solution into their business process COSTS much more than the cost of creating an AI system.
Situations like this often happen due to the poor communication between those who are directly involved in the business process and those who innovate.
Encourage AI developers to get out of their lab and go into the “field” as soon as possible to interact directly with the expected users of the system!

#4. Most AI solutions are useless, because, internally, people don’t use them

AI system developers typically do not like to go out into “the real world.” For example, in agriculture, often when an AI system is created, it is implied that the AI developer used “STANDARD machine learning approaches on some pictures and got some result.”

Everything seems to be just fine – an AI system was successfully created after all. When the results from using a system like this get into the hands of an expert (for example, an agronomist), they happen to be absolutely useless to him.

Of course, the “let’s invite an AI shaman to create an AI system using standard machine learning methods” approach is cheap and can give useful results, but, typically, in my practice, the results are going to be useless. To get really valuable results, the AI system developers need to dive deep into the subject area and understand all the nuances. This way they can create neural networks, which as a RESULT will be able to compete with the existing neural networks of specialists in this specific field who have studied it as their major for 5-6 years and then practiced it for ten years.

#5. 50 to 70% of problems/tasks can be solved more efficiently without using “AI”

Nowadays, a lot of AI startups are trying to offer silver bullets to a variety of tasks that have been done effectively using well-known methods that do not require AI (simple statistical methods, for example).

Therefore, before developing any AI system, it is necessary to calculate the cost of its creation and OPERATION and to make sure that it is predictably more effective than currently existing solutions – if the system can only provide an improvement that is within a margin of error, then there is no point in creating it.

Instead of the conclusion

Overall, I would recommend large corporations to stop “worshiping” AI “shamans” and begin applying the same decision-making and management methods to AI projects as they do to others.
There is no “magic” in modern AI (CV / ML, Deep Learning); therefore AI projects should be carried out according to planned budgets and schedules: =)

Vitaliy Goncharuk

vactivity @

M&A of a tech start-up: How to resolve the conflict of interests between investors and technology co-founders?

For the last 4 years, I was involved in various roles in 5 processes of M&A of technology startups.

Every time I observed the same conflict of interests between investors and a core tech team/co-founders because in every technology startup there are 3 groups of stakeholders with different interests:
1. Investors;
2. Investment banker, legal and accounting teams;
3. Co-founders/technology team who developed the core IP that is the subject of acquisition.

Usually, by the time the question of M&A is raised co-founders/technology team have already dedicated more than 4 years of their life to the startup, but they never get all their shares at closing. Therefore they have to work for the additional 1+ years to receive all the money from the deal (shares + stock options), as well as the core technology team has to sign a non-compete agreement for 1+ years and other obligations.

At the same time, other 2 groups (investors, IB, legal and accounting teams) receive money immediately at closing without any additional obligations and restrictions, thus their only interest is to get money as soon as possible.

It means that if, for example, a founder owns 50% of the company and an investor just 20%, at closing of the deal the investor will receive 20% of the price, but the founder could receive LESS than the investor as the acquirer is usually interested in motivating the founder to work as long as possible in the acquirer’s company. Also, the founder has to spend the additional time of his life for this business project comparing to the investor.

Usually after signing the term sheet beneficiaries that get money immediately at the closing start to push other groups to sign any non-compete terms, limited terms of Good Reason resignation, and very long obligatory time to work for the acquiring company.

How to avoid such conflicts of interest?

From my experience I see only one way – all these conditions should be incorporated in the term sheet.

As soon as all these conditions are in the basic deal document the temperature of such conflict of interests lowers significantly.

Good luck with business and M&As to everyone!:=)

Best regards,

Vitaliy Goncharuk

v @

Computer Vision in Eastern Europe: Bunch of Cool Researchers & Engineers, but Lack of Big Challenging Projects

I live and run a business in Silicon Valley ( – SLAM and CV for Robots and AR / VR, est. 2011), but since 2012 I spend a part of my time to the systematic development of CV / ML in Eastern Europe:

 – Since 2014 I have been holding a conference on Computer Vision and Machine Learning that gathers the largest community of  CV/ML Researchers and Engineers (more than 1700) – EECVC (web –;

 – With a group of activists we popularize CV/ML specialties, including active work on the opening of labs and majors in universities (MSc of computer vision, etc.).

– I manage a stealth community of angel investors from the United States interested in investing in CM / ML startups and cooperate with R&D centers in Eastern Europe;

After Amazon’s acquisition of Ring for 1 billion dollars with R&D office in Eastern Europe, the interest in opening R&D centers in this region rose significantly – everyone is impressed by the fact that Ring Labs could grow from 10 people to 500 (!!!!) in 2 years, which is almost impossible to do in Silicon Valley with the same level of new employees.  Continue reading “Computer Vision in Eastern Europe: Bunch of Cool Researchers & Engineers, but Lack of Big Challenging Projects”

Will employers “hire” neural networks /robots instead of Harvard/Stanford students?

July 9-10, 2016 – was a wonderful and very interesting weekend: on Saturday I organized the Eastern European Computer Vision Conference, and on Sunday I held a private event for 20 people with INCOSE Russian chapter research director to discuss the burning issues in the field of Systems Engineering.

A lot of conclusions after such intellectual weekend have been made.

The most interesting of those that can be published is the following:

The education system in the last years has been actively discussing issues of reforms and changes in teaching methods, but nothing really revolutionary has been offered – it is mainly the “imitation” of changes and reforms.

Why do I think so? Continue reading “Will employers “hire” neural networks /robots instead of Harvard/Stanford students?”

Virtual Reality could be the Best Visual Interface for Drones

Originally published at – Virtual Reality could be the Best Visual Interface for Drones 

As you may know, there will be a rapid utilization of drones for commercial purposes (products delivery, inspections, other commercial services, etc.) in the next 2–3 years.
In order to provide services in different areas drones will require either completely autonomous navigation or manual co-piloting, meaning human labor.

For the last 3 months we have been experimenting in our lab with more natural interfaces for the manual drone control. We expect that they can minimise the risk of crashing and increase the accuracy of co-piloting due to clarity and intuitive interface, which will be based on our navigational system and SLAM SDK.

One of the most interesting and intuitive interface ideas is to use virtual reality headset together with the gesture recognition sensor(like Leap Motion):


View in the headset: Continue reading “Virtual Reality could be the Best Visual Interface for Drones”

Early investors in B2B startups pay for free pilots for big empires

In the last 4-5 years, you could observe an investment boom in B2B startups.

It has become a great business: attract investments, make a product/technology  and sell the company to a major technological Empire.


The popularity of this model can be probably explained by the bigger profitability corporations get from these external investments compared with in-house investment in R&D. Continue reading “Early investors in B2B startups pay for free pilots for big empires”

Boom in AR/VR as a result of global competition in mobile industry

In the last 1-2 years, we have been witnessing an active interest on the part of global corporations, such as Google, Samsung, Apple etc to the area of Augmented Reality and Virtual Reality.

What causes such close attention to our sphere in the recent years and why corporations were not particularly interested in developments in the field of VR and AR before?

In my opinion, in the 90s world producers of “personal electronics” only slightly competed with each other and engaged more in the expansion in local markets – for example Nokia was almost unknown in the United States, while Motorolla almost was not represented in the European market.

Prior to 2003-2004, these corporations were securing markets, teaching consumers how to use smartphones and in fact were creating very similar platforms and technologies.

With the emergence of iPhone from Apple the market essentially got the first universal platform that provides services and deliver content to customers. It has become popular in all markets, which qualitatively changed the global nature of how companies work in mobile industry.

As a result, instead of expansion in local markets we got global competition. Those who could not scale its business left the market.

If we analyze the development of mobile phones, the market share of major players in the last 2-3 years, we can see that the period of expansion ended for them and they started competing very harshly with each other in terms of “burning marketing budgets,” which results in the decreases of their margins. There is nothing fundamentally new that has changed in smartphones – the competition is in the “screen size” and additional services, which in fact are quite simple to add.

What is the easiest method to get away from the direct and unfavorable competition?
That’s right – start developing adjacent areas or even better – create new markets.

One of these promising new markets is VR and AR.

It is our sphere of VR and AR that is slowly, but steadily was able to create the prototype devices just by the time the open competition among the major manufacturers of smartphones started. These prototypes allow to deliver content and to offer new services to consumers more effectively (not in 2D, but in 3D), but even more importantly IN LARGE SCALE.

Therefore, the major manufacturers of smartphones have started actively invest in this area, realizing that the next battle for the consumers’ wallets will not be at arm’s length, but directly in front of consumers’ eyes.

Well, we can only increase our efforts to develop the most organic devices and interfaces in VR and AR.

Due to the growing competition in the VR and AR between large corporations the best companies in VR and AR will get an opportunity to reach out to consumers and become popular among them by creating an entirely new reality or by augmenting it!

Best regards,


Vitaliy Goncharuk

v @

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