quantumblack
Enabling MLOPs in Three Simple Steps
I recently engaged in a project involving the implementation of a multiclass classification prediction system utilising financial transactional data, comprising over 10 million records and over 70 classes. Through this project, I constructed a streamlined end-to-end machine learning operations (MLOPs) infrastructure that is well-suited for this specific use case, while maintaining cost efficiency. The term MLOPs has a broad range of concepts and definitions, as offered by various vendors or solutions. Some focus on aspects such as training traceability and experimental tracking, while others prioritise feature storage or model deployment. In my understanding, MLOPs is the entire end-to-end process, from data extraction to model deployment and monitoring.
New McKinsey survey reveals the AI tech-talent landscape
January 20, 2023After five years of steady, sometimes heady, growth, AI adoption has plateaued, according to The state of AI in 2022, our annual survey of 1,500 companies. Use cases are stable, and the market for tech talent is tight, with new "hot jobs" surfacing every year. But much remains to be done about managing risk and building inclusive teams. "After a period of initial exuberance, we have reached a plateau, a course we've observed with other technologies in their early years of adoption," says partner Michael Chui. He authored the research with senior partners and QuantumBlack, AI by McKinsey leaders Alex Singla and Alex Sukharevsky; partner Helen Mayhew; and associate partner Bryce Hall.
Stop investing so much in A.I. technology. Invest more into what helps you create A.I. applications faster and easier
The percentage of companies adopting A.I. has been plateauing between 50% and 60% over the past few years. Meanwhile, some leaders have shared their frustration over not yet seeing the level of returns from A.I. investments that they expected. They simply haven't been able to get it to scale. Are some companies forgoing the pursuit of A.I.? Significant returns are being realized by leading companies. There is a contingent that is seeing substantial revenue boosts and 20% or more of their earnings before interest and taxes (EBIT) come from A.I. as they apply the technology to improve decisions, speed processes, and automate mundane, repetitive tasks, freeing workers to explore innovations that can vault an organization into entirely new business arenas.
McKinsey named a Leader in AI Service Providers by Forrester
December 1, 2022McKinsey has been named a Leader, the highest designation, in The Forrester Wave: AI Service Providers, Q4 2022 report. Forrester evaluated 12 firms, assessing them on 29 criteria grouped into the categories of current offering, strategy, and market presence. We received the highest possible rating in criteria including AI talent, vision, and market approach. "McKinsey & Company leads enterprises with end-to-end AI transformation," the Forrester report notes, also recognizing that "McKinsey addresses AI holistically: as a technology, an operational model, and a strategic asset." The report also notes that McKinsey "[places] a heavy emphasis on ROI." McKinsey acquired the AI arm of our firm, QuantumBlack, in 2015, and the Forrester report points out that this move "continues to deliver top-notch data science talent."
Maximizing the Potential of AI for Business
Artificial Intelligence is high on the agenda of CEOs in many prominent organizations worldwide. The adoption of AI by business leaders continues apace, and its impact on the bottom line is growing. McKinsey research shows that most firms have adopted artificial intelligence in at least one of their business functions--up from 50 percent in 2020. Moreover, nearly two-thirds of respondents say their companies' investments in AI will continue to increase over the next three years, suggesting we're just in the early stages of the AI revolution. Only 11 percent of the businesses succeeded in bringing AI into the production phase, scaling it within their companies and integrating it into their DNA.
An AI power play: Fueling the next wave of innovation in the energy sector
Tatum, Texas might not seem like the most obvious place for a revolution in artificial intelligence (AI), but in October of 2020, that's exactly what happened. That was when Wayne Brown, the operations manager at the Vistra-owned Martin Lake Power Plant, built and deployed a heat rate optimizer (HRO). Vistra Corp. is the largest competitive power producer in the United States and operates power plants in 12 states with a capacity of more than 39,000 megawatts of electricity--enough to power nearly 20 million homes. Vistra has committed to reducing emissions by 60 percent by 2030 (against a 2010 baseline) and achieving net-zero emissions by 2050. To achieve its goals, the business is increasing efficiency in all its power plants and transforming its generation fleet by retiring coal plants and investing in solar- and battery-energy storage, which includes the world's largest grid-scale battery energy-storage facility.
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AI and the super app: An interview with Careem's Selim Turki
QuantumBlack, AI by McKinsey recently sat down with Selim Turki, head of data and AI at Careem, to discuss the latest trends in advanced analytics and artificial intelligence. Far from a dry discussion of theory, the conversation coalesced around several fascinating use cases in which Careem is using AI to make a difference in people's lives. We discussed how AI is being leveraged to improve customer and driver security through targeted facial-recognition checks to ensure drivers (captains) are who they say they are. We also discussed how AI is being used to provide customers with the most accurate and up-to-date estimated times of arrival (ETAs) by factoring in a host of conditions, including local weather conditions, prayer times, and even iftar times during Ramadan. Along the way, we discussed what it means to be an "AI first" company and the outlook for AI tech--and talent--in the region.
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An AI power play: Fueling the next wave of innovation in the energy sector
Tatum, Texas might not seem like the most obvious place for a revolution in artificial intelligence (AI), but in October of 2020, that's exactly what happened. That was when Wayne Brown, the operations manager at the Vistra-owned Martin Lake Power Plant, built and deployed a heat rate optimizer (HRO). Vistra Corp. is the largest competitive power producer in the United States and operates power plants in 12 states with a capacity of more than 39,000 megawatts of electricity--enough to power nearly 20 million homes. Vistra has committed to reducing emissions by 60 percent by 2030 (against a 2010 baseline) and achieving net-zero emissions by 2050. To achieve its goals, the business is increasing efficiency in all its power plants and transforming its generation fleet by retiring coal plants and investing in solar- and battery-energy storage, which includes the world's largest grid-scale battery energy-storage facility.
- Energy > Power Industry (1.00)
- Energy > Energy Storage (0.95)
- Government > Regional Government > North America Government > United States Government (0.47)
- Leisure & Entertainment > Sports > Hockey (0.40)
Why hybrid intelligence is the future of artificial intelligence at McKinsey
April 29, 2022In 2015, McKinsey acquired QuantumBlack, a sophisticated analytics start-up of more than 30 data scientists, data engineers, and designers based in London. They had made their name in Formula 1 racing, applying data science to help teams gain every possible advantage in performance. Healthcare, transportation, energy, and other industry clients soon followed. Many times, acquisitions melt quietly into the parent company. This isn't the case for QuantumBlack; it has been an accelerating force for our work in analytics.
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QuantumBlack
October 28, 2020 – Developing artificial intelligence and analytics applications typically involves different processes, technology, and talent than those for traditional software solutions. Executives who possess a solid understanding of the basics can ensure they're making the right investments in their tech stacks and teams to build reliable solutions at scale. We've created an interactive guide to help.