There is a new opportunity with IBM Watson. It is a quasi competition for IBM partners. Fasmicro Group runs a business which is a member of IBM PartnerWorld and has all the details through IBM Partner Communications.If you are one, now is the time to apply. It could be rewarding.

In 2016, IBM did something extraordinary, engaging nearly 75 percent of IBMers from 115 countries and every business unit in the IBM Cognitive Build. The Build challenged IBMers to learn about cognitive, form teams, brainstorm and propose cognitive solutions. Ultimately, some of them developed prototypes and pitched those solutions in an IBM-internal event, not unlike Shark Tank. They created 2,700 cognitive ideas and hundreds of viable prototypes, and acquired valuable new skills.

Now they want to tailor this experience for you by creating the Watson Build for Business Partners. In the challenge, you can start your cognitive business journey by learning more about cognitive solutions like Watson and the IBM Cloud platform that supports cognitive workloads. Plus, your business will benefit by learning how to use Watson to build cognition into a product or service.

Challenge yourself to deliver and along the way they’ll help you develop useful skills that can accelerate innovation and benefit your clients—such as:

• Understanding and using IBM Watson APIs
• Applying data sets
• Gaining new ways of working and new tools
• Selling your solution on IBM Marketplace

This is a challenge you don’t want to miss. If you’ve wondered where IBM Watson and IBM Bluemix can take your business, the Build is your opportunity for guided discovery. If you’ve already developed an outstanding solution, find out how to participate in the Build and see how you can be recognized as the best.

Enhancements

This is a new email from IBM to its PartnerWorld members.

Since announcing the IBM Watson Build at the PartnerWorld Leadership Conference in mid-February, IBM Business Partners have been busy crafting their business plans and attending local Watson Build Workshops. The energy associated with the build is extremely positive, and we’ve heard from Business Partners, like you, that you’re submitting not one business plan, but multiple plans. So, we’ve expanded and enhanced the Watson Build program to give you more time to build out your plan. Plus, we’ve added even more opportunities for you to WIN. Learn more about enhancements to the Build:

1. The deadline to submit your business plan for judging is now Tuesday 30 May at 21:00 UK / 22:00 CET.
2. They’ve expanded the award opportunities. Now, one Business Partner from each of the seven geographies will have a chance to compete in the final round. Plus, they’re throwing in a wildcard round for a chance for a Business Partner from any of the geographies to compete for a spot in the final round. Eight Business Partners will now have a chance to compete for the title of Watson Build global champion.

Now begin the journey. You need a PartnerWorld account to apply.

Africa Tech Pitch LDN is a video pitch competition providing an opportunity for African tech startups to showcase their solutions to the London Tech ecosystem. The organizers are looking for high-impact, high-growth startups that are using technology to unlock untapped opportunities and address a real need in the African market.

The top 5 selected startups will be showcased during London Tech Week at an exclusive reception on 13th June, organised in partnership with Tech London Advocates, an influential community of over 4000 tech leaders, experts and investors.

The final winner will be selected and announced at the Africa Technology Business Forum London on 21st June, a gathering of Africa-focused global tech innovators, business leaders and investors.

If you are an ambitious tech startup in Africa looking to showcase your innovation on the global stage and connect with the London tech ecosystem then apply today!

Application criteria
• You are an Africa-focused technology startup with a unique proposition serving the African market
• You have already launched in the market and are able to demonstrate some traction
• You have a high-growth business model which has potential to scale across borders
• Your solution has capacity to improve and impact the lives of those it serves

Application deadline is Midnight on 31st May 2017

To apply, click here.

In 2006, Netflix created an open competition that would pay the winning data scientist a $1m prize. The task was to build a model that could outperform Netflix’s recommendation engine by 10%.

The winning team used an advanced machine learning technique known as “random forest,” which is now commonly used to optimize for predictive power.  This incredible boost in predictive power, however, came at the cost of interpretability. While the winning algorithm best predicts how the next thousand users will rate various films, it cannot directly explain why Henry from Kansas enjoys Space Jam.

When it comes to fintech, “black box” A.I. is often impractical. Traditional players such as banks or insurance carriers may feel uneasy, and imagine telling a regulator you denied someone a loan because “the model said so.” 

As a result, the most successful machine learning applications in fintech may be those that leverage unique alternative datasets, rather than the cutting edge of artificial intelligence.

Financial technology, also known as fintech, is an industry composed of companies that use new technology and innovation with available resources in order to compete in the marketplace of traditional financial institutions and intermediaries in the delivery of financial services. Financial technology companies consist of both startups and established financial and technology companies trying to replace or enhance the usage of financial services of incumbent companies.

That is why fintech will lag in pioneering AI because explaining to regulators that all decision making has been moved to models will be challenging in the foreseeable future. Regulators expect financial institutions to be making decisions by humans with machines supporting.

So even if you use machines, you need to have a clear understanding of the result so that humans can explain same to regulators. The implication is that if the models deliver great results and you cannot explain same. you cannot deploy them. That means your AI cannot be pioneering to the extent that humans cannot understand what is going on.

Fintech AI will lag voice, search, and other related areas which are not as heavily regulated as finance.