Jul 20, 2021

Microsoft launches HAX human-AI toolkit

Catherine Gray
3 min
Microsoft has released the Human-AI eXperience (HAX) toolkit to support companies when creating AI systems that interact with people.

This new toolkit provides a set of practical tools to help teams strategically create and responsibly implement best practices when creating AI technologies. Consisting of four components, the HAX toolkit is designed to help AI creators take a human-centred approach in their day-to-day work.

Microsoft HAX: helping AI creators

Discussing the toolkit, Senior Principal Research Manager at Microsoft Research, Saleema Amershi said: “Human-centeredness is really all about ensuring that what we build and how we build it begins and ends with people in mind. We started the HAX Toolkit to help AI creators take this approach when building AI technologies.”

Coming at a time where AI-infused services are becoming increasingly popular, Microsoft’s HAX toolkit provides support to companies wanting to iron out any inconsistencies and errors in their AI systems.

Microsoft HAX: responsible guidance

Although AI technology is useful to its users, there can be issues with understanding voice commands and/or interpreting pictures correctly. These inconsistencies within AI technology have resulted in AI developers being pushed for responsible guidance.

The new HAX toolkit provides developers with practical tools that translate human-AI interaction knowledge into accountable guidance.

Designed to assist a team throughout the user design process from planning to testing, the four components of the HAX toolkit are:

  • The Guidelines for Human-AI Interaction, which provides best practices for how AI applications should interact with people.
  • The HAX Workbook helps teams prioritize guidelines and plan the time and resources needed to address high-priority items.
  • The HAX Design Patterns offer flexible solutions for addressing common problems that come up when designing human-AI systems. With it comes the HAX Design Library which is a searchable database of the design patterns and implementation examples.
  • Teams can also utilize the HAX Playbook to identify and plan for unforeseen errors, such as a transcription error or false positive.

Guidelines for success

Allowing for human collaboration to build better AI systems, the HAX toolkit allows for the creation of fluid and responsible human-AI experiences. This has evolved from a set of 18 guidelines, based on more than 20 years of research.

From its extensive research into human-AI experience, Microsoft recognised the need for companies to bring their guidelines into their workflow early, to have a real impact. 

Keen to set themselves apart from other existing human-AI interaction resources, the HAX team created specific guidelines for users to follow. This is opposed to more traditional resources that lean toward tutorials. 

As well as the practical tools within the HAX toolkit, the guidelines can also be utilised throughout the development lifecycle.

Divided into four groups, the guidelines are based on when they are most relevant to an interaction with an AI system:

  • Initially
  • During interaction 
  • When the AI system gets something wrong and needs to be redirected
  • Over time

These guidelines allow for a flexible approach to nurture continuous improvement when curating AI systems. They can help users identify and address issues proactively and systematically rather than troubleshooting when the system encounters a failure situation.

Encouraging users to share their feedback on the toolkit, Amershi said: “We are hoping this can be a trusted resource where people can go to find tools throughout the end-to-end process. We will continue to update and create new tools as we continue to learn and work in this space.

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Aug 3, 2021

Nvidia’s platform for AI startups passes 8,500 members

2 min
Nvidia has announced it is tracking more than 8,500 AI startups through its Inception AI startup programme

NVIDIA Inception, an acceleration platform for AI startups, has now surpassed 8,500 members. That’s about two-thirds of the total number of AI startups worldwide, as estimated by Pitchbook.

NVIDIA Inception is a programme built to accommodate every startup that is accelerating computing, at every stage in their journey. All programme benefits are free of charge and startups never have to give up equity to join.

Since Inception’s launch in 2016, it has grown more than tenfold. With total cumulative funding of over $60 billion and members in 90 countries, NVIDIA Inception is one of the largest AI startup ecosystems in the world. Growth has accelerated year over year, with membership increasing to 26% in 2020, and reaching 17% in the first half of 2021.


Data from across the world


Inception figures show the United States leads the world in terms of both the number of AI startups, representing nearly 27%, and the amount of secured funding, accounting for over $27 billion in cumulative funding. 42% of US-based startups were in California, with 29% in the San Francisco Bay Area. 

Behind the US is China, in terms of both funding and company stage, with 12% of NVIDIA Inception members based there. India comes in third at 7%, with the UK right behind at 6%.

AI startups based in the US, China, India, and the UK account for just over half of all startups in NVIDIA Inception. Following in order after these are Germany, Russia, France, Sweden, Netherlands, Korea and Japan.


Industry acceleration


In terms of industries, healthcare, IT services, intelligent video analytics (IVA), media and entertainment (M&E) and robotics are the top five in NVIDIA Inception. AI startups in healthcare account for 16% of Inception members, followed by those in IT services at 15%. 

More than 3,000 AI startups have joined Nvidia Inception since 2020. “Some countries are accelerating their ecosystem of AI startups by investing money and encouraging the local players to create more companies,” said Serge Lemonde, global head of Nvidia Inception, in an interview with VentureBeat.

“In our programme, what we are looking at is to help them all,” Lemonde said. “The lesson here is really having this window on the landscape and helping the startups all around the world — [this] is helping us understand the new trends. We can help more startups by developing our software  and platforms for the upcoming trends.”

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