This collaboration combines Tech Mahindra’s range of AI offerings, TechM amplifAI0->∞, and IBM’s watsonx AI and data platform with AI Assistants.

Customers can now combine IBM watsonx’s capabilities with Tech Mahindra’s AI consulting and engineering skills to access a variety of new generative AI services, frameworks, and solution architectures. This enables the development of AI apps in which organisations can use their trusted data to automate processes. It also provides a basis for businesses to create trustworthy AI models, promotes explainability to help manage risk and bias, and enables scalable AI adoption across hybrid cloud and on-premises environments.

According to Kunal Purohit, Tech Mahindra’s chief digital services officer, organisations focus on responsible AI practices, and incorporating generative AI technologies to revitalise enterprises. 

“Our work with IBM can help advance digital transformation for organisations, adoption of GenAI, modernisation, and ultimately foster business growth for our global customers,” Purohit added.

To further enhance business capabilities in AI, Tech Mahindra has established a virtual watsonx Centre of Excellence (CoE), which is already operational. This CoE functions as a co-innovation centre, with a dedicated team tasked with maximising synergies between the two companies and producing unique offerings and solutions based on their combined capabilities.

The collaborative offerings and solutions developed through this partnership could help enterprises achieve their goals of constructing machine learning models using open-source frameworks while also enabling them to scale and accelerate the impact of generative AI. These AI-driven solutions have the potential to aid organisations enhance efficiency and productivity responsibly. 

Kate Woolley, GM of IBM Ecosystem, emphasised the collaboration’s potential, adding that generative AI may serve as a catalyst for innovation, unlocking new market opportunities when built on a foundation of explainability, transparency, and trust. 

Woolley said: “Our work with Tech Mahindra is expected to expand the reach of watsonx, allowing even more customers to build trustworthy AI as we seek to combine our technology and expertise to support enterprise use cases such as code modernisation, digital labour, and customer service.”

This collaboration aligns with Tech Mahindra’s continuous endeavour to transform enterprises with advanced AI-led offerings and solutions, including their recent additions like Vision amplifAIer, Ops amplifAIer, Email amplifAIer, Enterprise Knowledge Search offering, Evangelize Pair Programming, and Generative AI Studio.

It is worth mentioning that the two companies have previously collaborated. Earlier this year, Tech Mahindra announced the opening of a Synergy Lounge in conjunction with IBM on the company’s Singapore campus. This Lounge seeks to accelerate digital adoption for APAC organisations. It aids in operationalising and leveraging next-generation technologies such as AI, intelligent automation, hybrid cloud, 5G, edge computing, and cybersecurity.

Beyond Tech Mahindra, IBM watsonx has been used in other collaborations to speed up the deployment of generative AI. Also happened early this year, the GSMA and IBM announced a new partnership to support the use and capabilities of generative AI in the telecom industry by launching GSMA Advance’s AI Training program and the GSMA Foundry Generative AI program.

In addition, there is a digital version of the program that covers both the commercial strategy and technology fundamentals of generative AI. This initiative uses IBM watsonx to provide hands-on training for architects and developers seeking in-depth practical generative AI knowledge.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The extended partnership between Wipro and IBM combines the former’s extensive industry expertise with IBM’s leading AI innovations. The collaboration seeks to develop joint solutions that facilitate the implementation of robust, reliable, and enterprise-ready AI solutions.

The Wipro Enterprise AI-Ready Platform harnesses various components of the IBM watsonx suite, including watsonx.ai, watsonx.data, and watsonx.governance, alongside AI assistants. It offers clients a comprehensive suite of tools, large language models (LLMs), streamlined processes, and robust governance mechanisms, laying a solid foundation for the development of future industry-specific analytic solutions.

Jo Debecker, Managing Partner & Global Head of Wipro FullStride Cloud, said: “This expanded partnership with IBM combines our deep contextual cloud, AI, and industry expertise with IBM’s leading AI innovation capabilities.”

A key aspect of this collaboration is the establishment of the IBM TechHub@Wipro, a centralised tech hub aimed at supporting joint client pursuits. This initiative will bring together subject matter experts, engineers, assets, and processes to drive and support AI initiatives.

Kate Woolley, General Manager of IBM Ecosystem, commented: “We’re pleased to reach this new milestone in our 20-year partnership to support clients through the combination of Wipro’s and IBM’s joint expertise and technology, including watsonx.”

The Wipro Enterprise AI-Ready Platform offers infrastructure and core software for AI and generative AI workloads, enhancing automation, dynamic resource management, and operational efficiency in the enterprise. Moreover, it caters to specialised industry use cases, such as banking, retail, health, energy, and manufacturing, offering tailored solutions for customer support, marketing, feedback analysis, and more.

Nagendra Bandaru, Managing Partner and President of Wipro Enterprise Futuring, highlighted the flexibility of the platform, stating: “Wipro’s Enterprise AI-Ready Platform will allow clients to easily integrate and standardise multiple data sources augmenting AI- and GenAI-enabled transformation across business functions.”

In addition to facilitating AI governance through the AI lifecycle, the platform prioritises responsible AI practices, ensuring transparency, data protection, and compliance with relevant laws and regulations.

As part of this collaboration, Wipro associates will undergo training in IBM hybrid cloud, AI, and data analytics technologies, further enhancing their capabilities in developing joint solutions.

(Photo by Carson Masterson on Unsplash)

See also: Reddit is reportedly selling data for AI training

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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The geospatial model, built from NASA’s satellite data, will be the largest of its kind on Hugging Face and marks the first-ever open-source AI foundation model developed in collaboration with NASA.

Jeff Boudier, head of product and growth at Hugging Face, highlighted the importance of information sharing and collaboration in driving progress in AI. Open-source AI and the release of models and datasets are fundamental in ensuring AI benefits as many people as possible.

Climate science faces constant challenges due to rapidly changing environmental conditions, requiring access to the latest data. Despite the abundance of data, scientists and researchers struggle to analyse the vast datasets effectively. NASA estimates that by 2024, there will be 250,000 terabytes of data from new missions.

To address this issue, IBM embarked on a Space Act Agreement with NASA earlier this year—aiming to build an AI foundation model for geospatial data.

By making this geospatial foundation model openly available on Hugging Face, both companies aim to promote collaboration and accelerate progress in climate and Earth science.

Sriram Raghavan, VP at IBM Research AI, commented:

“The essential role of open-source technologies to accelerate critical areas of discovery such as climate change has never been clearer.

By combining IBM’s foundation model efforts aimed at creating flexible, reusable AI systems with NASA’s repository of Earth-satellite data, and making it available on the leading open-source AI platform, Hugging Face, we can leverage the power of collaboration to implement faster and more impactful solutions that will improve our planet.”

The geospatial model, jointly trained by IBM and NASA on Harmonized Landsat Sentinel-2 satellite data (HLS) over one year across the continental United States, has shown promising results. It demonstrated a 15 percent improvement over state-of-the-art techniques using only half the labelled data.

With further fine-tuning, the model can be adapted for various tasks such as deforestation tracking, crop yield prediction, and greenhouse gas detection.

IBM’s collaboration with NASA in building the AI model aligns with NASA’s decade-long Open-Source Science Initiative, promoting a more accessible and inclusive scientific community. NASA, along with other federal agencies, has designated 2023 as the Year of Open Science, celebrating the benefits of sharing data, information, and knowledge openly.

Kevin Murphy, Chief Science Data Officer at NASA, said:

“We believe that foundation models have the potential to change the way observational data is analysed and help us to better understand our planet.

By open-sourcing such models and making them available to the world, we hope to multiply their impact.”

The geospatial model leverages IBM’s foundation model technology and is part of IBM’s broader initiative to create and train AI models with transferable capabilities across different tasks.

In June, IBM introduced watsonx, an AI and data platform designed to scale and accelerate the impact of advanced AI with trusted data. A commercial version of the geospatial model, integrated into IBM watsonx, will be available through the IBM Environmental Intelligence Suite (EIS) later this year.

By leveraging the power of open-source technologies, this latest collaboration aims to address climate challenges effectively and contribute to a more sustainable future for our planet.

(Photo by Markus Spiske on Unsplash)

See also: Jay Migliaccio, IBM Watson: On leveraging AI to improve productivity

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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The features include generative AI commentary and AI draw analysis, aimed at enhancing the engagement and insight for tennis enthusiasts.

Usama Al-Qassab, Marketing & Commercial Director at The All England Club, said:

“We are constantly innovating with our partners at IBM to provide Wimbledon fans, wherever they are in the world, with an insightful and engaging digital experience of The Championships.

This year, we’re introducing new features for our digital platforms that use the latest AI technology from IBM to help fans gain even more insight into the singles draw and access commentary on a wider variety of matches through our match highlights videos.”

AI commentary

The AI commentary feature, developed in collaboration with IBM iX, offers fans watching match highlights videos the option to receive audio commentary and captions of key moments.

The tool aims to provide a more insightful experience when catching up on matches through the Wimbledon App and wimbledon.com. This introduction marks a step towards making commentary available for matches outside of Wimbledon’s Show Courts, which already have live human commentary.

Experts from IBM iX and The All England Club worked together to train the AI using foundation models from IBM’s enterprise AI and data platform, watsonx.

The generative AI employed in this feature produces narration with diverse sentence structures and vocabulary, enhancing the informative and engaging nature of the clips.

AI draw analysis

Another innovative feature introduced this year is the AI draw analysis, a first of its kind in tennis.

Leveraging AI, this feature provides a statistic to determine the favorability of the path to the final for each player in the singles draw. Factors such as match-ups against potential future opponents and the player’s position in the draw compared to competitors contribute to the player’s draw favorability rating.

This unique insight enables tennis fans to uncover anomalies and potential surprises in the singles draw that may not be evident solely by considering the players’ rankings. The feature aims to inspire more debate and engagement within the fan community.

Jonathan Adashek, SVP of Marketing and Communications for IBM, commented:

“IBM is bringing new layers of insight and engagement to the 2023 Championships through the use of innovative new tools, powered by foundation models and generative AI from watsonx.

We’ve seen first-hand how these technologies have the power to help major sporting events like Wimbledon to grow their audiences through outstanding digital experiences. 

The AI and data platform that IBM is using to create unique fan experiences for Wimbledon is the same technology that we’re using to drive business transformation with clients across all sectors and industries.”

These new features complement the existing suite of AI-powered tools available on the Wimbledon App and wimbledon.com. The suite includes the IBM Power Index Leaderboard, IBM Match Insights, and Personalized Highlights Reels and Recommendations.

These digital features leverage IBM’s Watson AI technology to analyse over 100,000 data points from every shot played throughout the tournament, providing fans with a deeper understanding of the players, their opponents, and likely outcomes. The constant updates and tailored insights keep fans engaged throughout the tournament.

Wimbledon will take place from July 3 to July 16, 2023. Fans can witness these AI-powered features in action by visiting wimbledon.com or downloading the Wimbledon App from the App Store or Play Store.

(Photo by Ariv Gupta on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.

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In 1997, IBM’s Deep Blue supercomputer was used to beat World Chess Champion Garry Kasparov. At the time, all too familiar headlines suggested that computers would soon replace humans. Over two decades later, AI has proven to be an assistive tool that benefits us every day.

IBM Watson’s first commercial application was announced a little over a decade ago in February 2013 for utilisation management decisions in lung cancer treatment. In the years since, we’ve seen it used to deliver game-changing advancements in healthcare, weather forecasting, education, science, and much more.

AI News caught up with Jay Migliaccio, Senior Product Manager for Watson Orchestrate, to learn how IBM is now using its vast experience to help businesses with their digital transformations.

AI News: So, Jay, can you tell me how IBM is helping businesses to improve the productivity of their workforces?

Jay Migliaccio: Yes, Ryan. Thanks so much for the invite and for asking me here.

IBM is expanding its suite of offerings in the area of digital labour. Digital labour leverages AI and automation to help workers become more productive. And, much like human labour, digital labour performs work on business systems through “skills”.

Digital labour skills enable digital labour to interact with business applications, much like you and I would interact with a system of record or system of engagement. We can do this now through digital labour. And, what’s new and unique, is that digital labour leverages the human-centric interaction style.

So, we’ve introduced natural language and we’ve also introduced intelligent orchestration to be able to execute not just single skills, but actually multiple skills to be able to achieve higher-level tasks.

AN: Generative AI is a hot topic in the market at the moment. Do you see that being used practically in the workplace and what risks should businesses be aware of?

JM: Yeah, great question. I actually do use it myself in the workplace, I occasionally have to develop software tools and simple scripts and I have had it generate a number of scripts for me successfully. So I’m impressed not just with its ability to generate verbal and written content, but also code content. I for sure believe it will become increasingly useful in the workplace.

Current generative AI platforms have been trained on the internet, so remember your results may vary. I know anytime I Google or search for things on the internet I take the results with a grain of salt.

I believe that enterprises, as they go to look and adopt generative AI systems, they’ll lean more towards AI that they can trust. Therefore, we need to work on being able to create that trust element in generative AI solutions.

AN: What is the value of Watson Orchestrate for developers?

JM: When we talk about developers, I’m talking about automation developers. And that’s by and large developers that are integrating apps and business apps and business systems to work together.

For the most part, those developers have been integrating business systems to business systems. Now what we can do with Watson Orchestrate is we can introduce the human into the loop.

These automation developers now have a platform where they can build and integrate their automation workflows and they can bring a human experience into these automation workflows for everyday human workers.

Watson Orchestrate provides a platform for creating human-centric workflow automation, designed to interact with humans in our native communication style which is spoken or written word.

AN: How does Watson Orchestrate learn from user interactions?

JM: There are a couple of ways Watson Orchestrate is monitoring the behaviour of humans and learning from them. 

Perhaps most important is its ability to interpret the natural language through which humans are communicating. Today it’s the written word, but in the future spoken word. Watson Orchestrate can not just do a pattern match based on existing known sentences, but it can actually understand the intent of those utterances. 

Additionally, it can extract entities from those utterances. So, when you use proper nouns in a sentence, it can understand that’s an entity that it would use as part of an automation. It can match the intent of the utterance to existing skills that it has and can react accordingly. It can understand the intent of the utterance and then take action on those skills. Increasingly, it can sequence multiple skills together.

Also, we are working on systems for empowering Watson Orchestrate to monitor the user’s behaviour. And, just like any modern SaaS application today that has recommendations based on your behaviour, we’re working on recommendation engines to recommend to employees how they can use Watson Orchestrate to be more productive in the future.

AN: Talking about AI more generally, what new ways of working are today’s advancements enabling?

JM: As I just alluded to, we’re increasingly empowering systems to understand human natural language to a much more complex and sophisticated extent. Natural language interpretation has grown way beyond the basic pre-programmed bot experience.

I’m sure everybody has had an experience on a website where there’s a bot responding to your basic questions. What we’re trying to do is make that bot much more intelligent. The current generation of digital labour can understand your intent, extract entities from your utterances, and, most importantly, take action on your behalf.

AN: On the flip side, what are some of the main dangers of automation tools and how do we overcome those?

JM: I’m not sure if this is a specific category of danger, but I suppose I would put it under the law of unintended consequences. Anytime you work with technology, there can be outcomes that you don’t expect.

For example, if we think about the automobile as an automation tool for moving humans around – the intent, of course, was to move a human from A to B faster, and maybe more reliably. But the net result is occasionally we have accidents.

Much like the way we build transportation systems to constrain and reduce the potential for accidents, we have to do the same thing in our business systems with digital labour. Certainly, we’re going to want to start small and just do very selective, very specific tasks that are well-curated and well-defined.

We’ll need to create guardrails that guard against unintended and unexpected behaviour. One of the ways we’re doing this in Watson Orchestrate is to empower the digital labour to act on the user’s behalf and therefore leverage the user’s credentials when interacting with business systems.

As an employee, I’m given certain access to a business system based on my role. Therefore, we know when the digital employee performs actions on my behalf it also has those existing restrictions and permissions for those business systems.

Another option is monitoring behaviour and monitoring for unintended consequences. And, lastly, integrating governance and creating policies that permit or restrict the behaviour of digital employees.

AN: Are you a believer in the metaverse? If so, how much work do you think we will be doing in it?

JM: Yeah, great question. Metaverse for me is a very loose term. Here we are digitally speaking – we’ve never met before, you could be an avatar for all I know. So, in that sense, I’m a believer in the metaverse.

For me, like most innovative technologies, it will start on the fringe and work its way into the mainstream. You can look at entertainment and gaming and see very metaverse-like experiences being used there.

I’ve seen examples of the metaverse being used for deep meditative experiences. If you want to go into deep meditation, you can put on your virtual headsets and enter a metaverse world that is very different from the physical world we live in.

And I also can see the metaverse being initially used for education purposes. I think it’s a great way – a sort of low-risk way – to introduce people to new environments and new ideas at scale.

I don’t think we’re gonna go to the metaverse to go to work. I don’t see that as something coming in the near term.

AN: I can only promise I’m not an avatar for the time being. I might bump into you at Digital Transformation Week, next week. You’ll obviously be in attendance, what will you be sharing with the audience at the event?

JM: Yeah, Digital Transformation Week I will be talking about our view on the digital labour market and some of our solutions. I will also be sharing some of the stories about the early adopters of IBM’s digital labour solutions.

You can watch our full interview with Jay below:

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Anadolu Insurance is using IBM technology for assessing its auto claims – specifically, the IBM Watson Visual Recognition service.

On average, Anadolu reviews around 1200 vehicle damage files each day. Manually checking each file was a slow and tedious process, but – with 63 percent contradicting the amount of described damage – it’s a vital operation.

Mehmet Abacı, Deputy Chief Executive Officer of Anadolu Insurance, said:

“Insurance is one of the primary industries that are affected by technological developments the most. As the largest and long-established company of Turkey, we are also a leader in the use of technology.

We want to reduce the analysis and repair processes to a few hours by using artificial intelligence in analysis of minor damages in our customers’ vehicles. Before that, we also performed such work and managed to pay our customers for minor housing damages such as glass breakage within five seconds. Now we have also started to use artificial intelligence technology in auto insurance more efficiently.

IBM Watson is helping Anadolu’s customers take optimal photos of their damaged vehicle. Affected parts are identified along with the scope of the damage for the AI to determine whether the parts need repair, replacement, or further expert consultation.

Volkan Sözmen, IBM Turkey Country General Manager, comments:

“We are proud that our long-standing collaboration with Anadolu Insurance has acquired a new dimension with this project. IBM Watson’s visual recognition capabilities will greatly contribute to making Anadolu Insurance’s processes more efficient and hassle-free for its customers.

We believe that this project will not only help the insurance industry gain new momentum, but also change the course of the digital transformation journey.”

Experts from Anadolu Insurance are working alongside IBM’s data scientists to train Watson with the language associated with damages and auto parts; such as buffer, door and mud-guards.

The insurance claims solution is expected to launch for contracted auto repair shops in the second half of this year.

Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

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The current ISS commander, German astronaut Alexander Gerst, was first to speak with CIMON. Gerst said “Wake up, CIMON” which prompted the robot to respond “What can I do for you?”

CIMON and Gerst’s first assignment was to perform a student-designed experiment with crystals. The robot, after recognising Gerst’s face and positioning itself autonomously, provided instructions on how to conduct the experiment.

On Earth, CIMON weight just five kilograms and was designed by Airbus. The orb-like robot has a large screen on the front which can either display cartoonish faces or information required for a particular task.

Till Eisenberg, CIMON Project Manager at Airbus, said:

“CIMON represents the realisation of an Airbus vision. It is a huge step forward for human space flight, achieved by working in cooperation with our partners.

With CIMON, we have laid the foundations for social assistance systems that are designed to be used under extreme conditions.”

IBM Watson provides the robot’s AI smarts for understanding questions. CIMON cannot process data itself and requires communication with a computer on the ground.

Matthias Biniok, IBM project lead on CIMON, commented:

“If CIMON is asked a question or addressed, the Watson AI firstly converts this audio signal into text, which is understood, or interpreted, by the AI.

IBM Watson not only understands content in context, it can also understand the intention behind it.

The result is a tailored answer, which is converted into speech and then sent back to the ISS, enabling a natural, dynamic spoken dialogue.”

Data is beamed to and from the ISS using the station’s WiFi network which uses satellites to communicate with the ground.

Bernd Rattenbacher, team leader of the ground control centre, explained:

“The data link to Earth is established via satellite to NASA/ESA and to the DLR’s Columbus control centre in Oberpfaffenhofen, Germany.

From there, the signal is transmitted to us, the CIMON ground station at BIOTESC in Lucerne [University], the Swiss User Support and Operations Center, which is connected to the IBM Cloud in Frankfurt over the internet.

The time needed for the signal to be transmitted via satellite is 0.4 seconds each way. A number of firewalls and VPN tunnels are in place to ensure data security.”

Despite the distance, CIMON is said to respond within a couple of seconds after a question is asked.

CIMON is considered to be a demonstration of what future human-robot interactions could look like on space missions – improving safety, and the ability to conduct more complex tasks and experiments.

 Interested in hearing industry leaders discuss subjects like this and their use cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, Blockchain Expo, and Cyber Security & Cloud Expo.

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IBM has already cemented its place as a leader in AI with Watson and its deep learning capabilities. Deep learning is a subset of AI which mimics the human brain and is therefore a focus of researchers.

Companies including Microsoft, Facebook, Amazon, and Google have made advancements in deep learning, but IBM’s could be the most groundbreaking. Today’s deep learning systems can take days to analyse data, but IBM has managed to reduce this to just hours.

IBM has achieved this by overcoming a core hurdle of deep learning systems. Most current projects are run on a single server due to how much data is involved and the difficulty of keeping it all synchronised. New software developed by IBM, however, claims to split deep learning tasks across 64 servers running up to 256 processors.

This is available to customers using IBM Power System servers or anyone interested in testing its capabilities. For its tests, IBM used 64 of their Power 8 servers which feature Intel microprocessors and NVIDIA GPUs linked with an NVLink connection. This configuration allows for rapid data flow between the chips.

Using this method, IBM claims performance can be boosted 50-60 times over a single server typically used today. However, it requires some complex work under-the-hood to take full advantage of the extra servers and processing power.

Managing traffic is the main priority to ensure all the processors are working and not sitting idle. Each processor has a dataset to work on but also requires data from other processors to understand the complete picture. Optimising this management of traffic is an ongoing process to achieve peak levels of performance.

A record breaker

In an ideal scenario, each processor added would deliver a 100 percent improvement to performance, but this is unrealistic. IBM claims its system achieved 95 percent across 256 processors, which is both impressive and sets a new record. The previous record was held by Facebook who achieved 89 percent.

This isn’t the only record IBM has claimed to have broken with their latest advancement. For image recognition, IBM says it observed a 33.8 percent accuracy rate analysing 7.5 million images over seven hours. The prior record was held by Microsoft with 29.8 percent accuracy, and that effort took 10 days to complete.

Are you impressed with IBM’s machine learning advancement? Share your thoughts in the comments.

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 Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London and Amsterdam to learn more. Co-located with the  IoT Tech Expo, Blockchain Expo and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

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