Aug

Reality of Bootstrapping

Going after investors? Do you know that less than 1 percent of startups actually raise VC (or angel) capital, which means that the vast majority are self-funded. Yet the main reason for it simply lies in the inability of most companies to find investors.

Bootstrapping, however, has several strategic advantages for your company's future growth. Perhaps the biggest is retaining the majority of shares and control over the strategy and direction your company is moving towards.

It also teaches financial discipline. Bootstrapping at the start helps to understand the importance of  revenue and cash flow, as opposed to unabridged product development, and keeps you connected to your company's financial reality. Only when profitability increase do you then green-light new opportunities, increased risk-taking, and growth acceleration.

In reality, the founders are expected to be flexible.  While entrepreneurs have certain intentions and philosophies when they are starting out, a hallmark trait for successful founders is the ability to adapt to changing environments and opportunities.

Sometimes, that means waiting a long time to generate the financial metrics that really matter, revenue and profit. By challenging your leadership team to focus on building the business organically and figuring out how to make the company consistently profitable on a model that can scale without VC capital, you make your company more valuable to future investors.

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Microsoft AI products

                                                 

Microsoft product strategy has always been and still remains that of ‘zero alternative’. Their ultimate policy is for their customers to have no choice but to embrace only Microsoft products. Consequently they created and are offering products and solutions in (almost) every segment of IT enterprise and consumer market, including, but certainly not limited to, their own data base, their own cloud services, operating system, office tools, programming language, and many more.

Not only do Microsoft offer wide variety of products, they tie them up together in a unified ecosystem that makes it easy for components to connect and interact. At the same time, this ecosystem is hostile to non-Microsoft products.

Microsoft strategy for the burgeoning, fast growing AI segment is similar:

Create products to address all parts of the AI market, add them to the ecosystem to ensure easy compatibility from within and difficulty of use from outside.

Currently the products on offer are:

- Microsoft AI engine, called LUIS. It is supposed to compete with other major industrial AI systems such as IBM Watson, and has similar training methodology. It offers webhook interfacing via endpoints.  

- Microsoft chatbot building platform, called, surprisingly, Microsoft Bot Platform. It addresses the popular demand for easy chatbot design and provides seamless connectivity with main user interfaces, such as web interface, SMS, mobile, and messaging platforms.

- In addition Microsoft offers their own messaging platform in Skype.

The main advantage of  using Microsoft AI products is the built-in connectivity with user interfaces.

The main disadvantage is in their ‘zero alternative’ policy - once you’ve chosen a Microsoft product you are likely will be forced to choose only Microsoft products for the duration of your project.

 

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AI unmasked: Have chatbots failed?

It is becoming increasingly popular to say that chatbots have failed and are overhyped.

While it is true that in many cases expectations from chatbots significantly exceed the results on the ground, the anticipation of chatbots’ demise are somewhat premature. 

One of the main problems for chatbots is that the market is inundated with low quality solution providers who deliver low quality results. This happened because conversational AI seems to have low entry barriers. Unlike other recent technological darlings such as space technology or renewable energy, conversational AI is purely software and therefore does not require vast sums of initial investment. 

What this approach is missing however,  is that conversational AI, in addition to being a software, also requires an accurate understanding of how language works. And there is a limited number of people in the world that do have such understanding.

When conversational AI is delivered by AI experts who understand the way human language works, the results are good and convincing, just as how you would expect them to be.

Suffering from unsatisfactory product quality is a common problem for many new and emerging industries.  The rules of the market dictate that most of the low quality players will eventually disappear. Poorly created chatbots will therefore not be around for too long.

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