Slowly but inevitably machine learning is starting to influence our daily lives. Whether you ask your home virtual assistant to check the weather forecast or cede some of the planning (and even driving) of your daily commute to your "smart" automobile, it is machine learning that is making life easier. Yet while we seem to have embraced machine learning at home, understanding and embracing its potential in the enterprise remains challenging. Judging by the experience I've had with our clients, the desire is there, experiments are happening, but there is difficulty in getting real change into production. Many organizations are not yet making the transformational changes driven from machine learning that will be needed in order to succeed in the coming years.

In today's business landscape, the value of a diverse workforce has become indisputable. Hard numbers support its positive impact on businesses' top and bottom lines. A recent survey revealed that 62% of participating executives rated diversity and inclusion as a high or top priority. Diverse organizations are often more successful than others. For example, McKinsey & Company found that gender-diverse organization are 15% more likely to outperform their peers, while ethnically-diverse organizations are 34% more likely to do so. With many of the world's leading economies facing an increasingly aging population, it is encouraging to see that retaining older workers can increase business productivity.

Rather than automating existing processes to make them faster and cheaper, true process reimagination forges new alliances between people and machines, enabling them to achieve more together. That's particularly salient for organisations in the public sector needing to reduce the risks they face. These new relationships are what Accenture calls the'missing middle'. Where machines help humans, there are three key dimensions. The first is where machines amplify or augment humans with new insights.

While you're asking yourself how to leverage your business on machine/deep learning, many questions come up from data collection, preparation, labeling, modeling, training, testing, continuous development, continuous integration... BuQuaTi's Machine Learning Platform (BQT-MLP) is the unique platform in the market which can serve all three Google TensorFlow models; TensorFlow, TensorFlow Mobile, TensorFlow Lite. Our professional services acompanied by our Machine Learning Platform (BQT-MLP) enable your smart digital journey end to end; simplification, preparation, modeling, development, deployment, operations, analytics. More than 60% of the efforts in a data project like Machine Learning, go into data preparation; cleansing, transforming, and labeling. We manage all aspects, and propose efficient, a-class solutions.

For the second straight year, Deloitte surveyed executives in the US knowledgeable about cognitive technologies and artificial intelligence,1 representing companies that are testing and implementing them today. We found that these early adopters2 remain bullish on cognitive technologies' value. As in last year's survey, the level of support for AI is truly extraordinary. These findings illustrate that cognitive technologies hold enticing promise, some of which is being fulfilled today. However, AI technologies may deliver their best returns when companies balance excitement over their potential with the ability to execute. To obtain a cross-industry view of how organizations are adopting and benefiting from cognitive computing/AI, Deloitte surveyed 1,100 IT and line-of-business executives from US-based companies in Q3 2018. All respondents were required to be knowledgeable about their company's use of cognitive technologies/artificial intelligence, and 90 percent have direct involvement with their company's AI strategy, spending, implementation, and/or decision-making. The respondents represent 10 industries, with 17 percent coming from the technology industry. Fifty-four percent are line-of-business executives, with the rest IT executives. Sixty-four percent are C-level executives--including CEOs, presidents, and owners (30 percent), along with CIOs and CTOs (27 percent)--and 36 percent are executives below the C-level.3 A year later, and the thrill isn't gone. In Deloitte's 2017 cognitive survey, we were struck by early adopters' enthusiasm for cognitive technologies.4 That excitement owed much to the returns they said cognitive technologies were generating: 83 percent stated they were seeing either "moderate" or "substantial" benefits.

Some major industries could soon be shaken up by a new development in artificial intelligence-- the technology's increasing portability. Chip manufacturers are making processors specifically for machine learning and related AI features, noted Deloitte analysts David Schatsky, Jonathan Camhi, and Aniket Dongre in a new report. In many cases, those chips are being designed to consume minimal power, making it possible for them to be used in small, portable devices. Meanwhile, AI software developers are designing new algorithms that can be run directly on such chips without ever needing to connect to computers in the cloud. The result is that we are about to enter an era that the analysts dubbed "pervasive intelligence," filled with devices and sensors that have AI technologies embedded within them.

Accenture ACN, 0.40% has invested in and formed a strategic alliance with Quantexa, a leading data analytics firm that provides technology solutions to uncover new intelligence. The minority investment made by Accenture Ventures will help Quantexa accelerate the development of its AI-powered entity resolution and network analytics technology working with Accenture Applied Intelligence. The new collaboration will help clients uncover new actionable insights across multiple industry use cases including fighting financial crime. As part of the alliance agreement, Accenture plans to build new capabilities that combine its technology and risk expertise with Quantexa's network analytics platform. The collaboration aims to develop multiple AI-enabled solutions addressing business challenges in areas including anti-money laundering, credit risk and customer insight.

Businesses that combine the capabilities of machines and humans together spur innovation, creating job openings such as artificial intelligence (AI) interaction designer, AI innovation strategist, AI personality trainer, and AI safety engineer. These jobs belong to the "missing middle," opportunities for organizations to bring people and machines together, said Paul Daugherty, Accenture's chief technology and innovation officer, during a talk at the Evanston campus's Kellogg Global Hub on October 30. More than 300 students, faculty, and staff listened to the author of the new book, Human Machine: Reimagining Work in the Age of AI. "We're at a point where it's really important to rethink our organizations and rethink the way we do business," Daugherty said. "We have the potential to really be entering an era of increased humanity and increased human potential, and that's why this is an especially important thing to get right as we think about it." Currently, businesses utilizing AI often evaluate how humans can help machines or how machines can help humans work, but Daugherty encourages organizations to think about how to embrace collaboration between humans and machines, rather than viewing them in opposition.

Business-to-consumer (B2C) businesses have made it a priority to incorporate machine learning into customer-facing functions, integrating it into sales and marketing. For business-to-business (B2B) companies, however, translating data into actionable marketing strategies can be a more difficult proposition. Selling to organizations invariably requires embarking on a much longer and more complex journey, culminating in an order of much higher value than in the consumer realm. With hundreds of thousands, if not millions, of dollars at stake, a misguided marketing investment could lead to financial losses. "The availability of data and the importance of having the focus on the full customer journey is coming a little later to the B2B world," says Laura Beaudin, a partner at Bain & Co. "A lot of expectations in terms of customers manifested themselves in the consumer world before they brought those expectations to their business-purchasing world."

Artificial intelligence (AI) may sound like science fiction, but it is real, and becoming increasingly important to companies in every sector. The field of artificial intelligence has produced a wide variety of "cognitive technologies" that simulate human reasoning and perceptual skills, giving businesses entirely new capabilities and enabling organizations to break prevailing tradeoffs between speed, cost, and quality. Aimed at a general business audience, this course demystifies artificial intelligence, provides an overview of a wide range of cognitive technologies, and offers a framework to help you understand their business implications. Some experts have called artificial intelligence "more important than anything since the industrial revolution." That makes this course essential for professionals working in business, operations, strategy, IT, and other disciplines.