IBM’s Watson AI is all about empowering you to accelerate your journey to AI. In his keynote at IBM Cloud Forum 2020, Sriram Raghavan, IBM’s Vice President of AI Research spoke about IBM’s approach to AI. This approach puts accessibility and scalability front and centre.
AI technology is revolutionising how organisations deliver value and increasing efficiency. This technology gives us the power to glean insights from vast amounts of data, automate tedious processes and better adapt to change.
In discussions around AI, technologists often forget the human element. How people use and interact with this technology becomes an afterthought. As a result, AI can seem impenetrable to the average person.
However, this is not the case with IBM Watson.
In his keynote at IBM Cloud Forum 2020, Sriram Raghavan shared IBM’s approach to all things AI. This approach centres on accessibility and scalability throughout all stages of the AI lifecycle.
Accelerate Your Journey to AI with AI Anywhere
When it comes to AI, IBM has a short and simple mission statement: To bring AI to where the data is, no matter where that data lives.
For this reason, IBM’s Cloud Pak for Data, built on the hybrid-cloud foundation of Red Hat OpenShift, allows data and AI capabilities to run on any cloud, integrated and managed via a single unified platform. This is a critical feature since it’s common for organisations to be running hybrid or multi-cloud environments.
It also brings an openness and transparency to data and insights, since it can be run wherever your data is.
IBM and Enterprise AI
Sriram Raghavan stressed that all of IBM’s AI is structured with enterprise usage in mind. All of their AI offerings fall into one of two categories:
- Tools for building, deploying and managing your own AI
- AI Infused applications that cover areas like customer service, IT operations, business performance management and enterprise automation
Accelerate Your Journey to AI with Holistic AI
What really stood out to me during the keynote was IBM’s holistic approach to AI. Their offerings address every stage of the AI life cycle.
These offerings include:
- Watson Knowledge Catalog: Used to prepare and organise data
- Watson Studio: Used to build and train AI models
- Watson Machine Learning: Used to deploy and run AI models
- Watson OpenScale: Used to monitor, manage and operationalise AI models
The Challenges of Adapting to AI
Obviously, adapting to AI isn’t without challenges. There are three friction points that can slow adoption of AI, and IBM is working to address each of these challenges.
Data Challenges
These kinds of challenges revolve around issues discovering and managing data, generally caused by segmented data silos, fragmentation of data, duplication and data hygiene issues.
Data automation helps to overcome these challenges. For example, IBM’s AutoAI capabilities are designed to automate and simplify the time-consuming processes of data prep and pre-processing so that organisations can instead focus on higher-value work like designing and deploying machine learning models.
Skills Challenges
One of the biggest obstacles to the adoption of AI, and cloud technology in general, is a lack of skills. Globally there is a scarcity of data science skills exacerbated by primitive tools for data that aren’t AI-ready. Not only is there a skills gap, but existing skills aren’t used efficiently, leading to wastage.
IBM is combating this through Data Science Automation. This makes data science tasks and workflows more accessible. It also prevents data science professionals from doing repetitive tasks that don’t take full advantage of their skills.
Operations Challenges
Ironically, the people and processes AI is designed to assist can become a barrier to adoption. In particular, it can be challenging to infuse AI automation into existing business and IT workflows. There are also issues around governance, risk management and compliance.
IBM is overcoming these challenges through Lifecycle Automation, which incorporates research innovation to help you address the management and continuous evolution of AI models.
To find out more about IBM Watson and the challenges and opportunities posed by AI tech, click here to tune into Sriram Raghavan’s talk on demand.
