Much ink has been spilled on the artificial intelligence (AI) race between the United States and China, leading to a whole lot of hand-wringing on how America can maintain its edge. America ought to double down on what it's best at: importing foreign talent. That's because among the main building blocks of a competitive AI ecosystem--data, policy, companies, and hardware--talent is the one area in which the United States definitively leads over China. Let's take a closer look at where America stands in terms of AI talent globally and the foundation of its current advantage. One metric to gauge AI talent is the attendees of the Conference on Neural Information Processing Systems, commonly referred to as NIPS within the industry.

Mezzanine.ai is a new approach for businesses looking to engage with machine learning. It empowers your data to be seamlessly and securely evaluated through multiple pre-trained machine learning models through a sophisticated, wizard-driven, orchestration and automation platform. By leveraging a multiplicity of machine learning models simultaneously, the detail and volume of data insights increase exponentially. Through its comprehensive application integration library, mezzanine.ai's Joshua Geist, Geminare's CEO, commented, "Machine learning is a transformational force for businesses, but like so many other technologies before it, access is limited to those with significant budgets and expert knowhow.

Mezzanine.ai was developed as a stand-alone solution through the utilization of Geminare's award winning and multi-patented orchestration and automation platform. As a leader in delivering data curation, resiliency and IT orchestration solutions, Geminare has helped advance global service providers with market leading orchestrated Cloud solutions, an example of which is the award-winning Resiliency Management Platform (RMP). Geminare is leveraging its capabilities to power the next generation of machine learning solutions for business.

Mezzanine.ai was developed as a stand-alone solution through the utilization of Geminare's award winning and multi-patented orchestration and automation platform. As a leader in delivering data curation, resiliency and IT orchestration solutions, Geminare has helped advance global service providers with market leading orchestrated Cloud solutions, an example of which is the award-winning Resiliency Management Platform (RMP). Geminare is leveraging its capabilities to power the next generation of machine learning solutions for business.

Under the microscope, both squamous cell carcinoma of the lung and squamous cell carcinoma of the head and neck appear as dense cell groups with non-specific growth patterns, making them impossible to distinguish based on tissue microstructure. But using artificial intelligence (AI), researchers developed a new classification method which identified the primary origins of cancerous tissue based on chemical DNA changes. The neural network achieved an accuracy over 99% when distinguishing between lung cancer and head and neck cancer, according to the findings of a study published in the journal Science Translational Medicine. "The bottom line is that we are solving a highly clinically relevant diagnostic problem by combining DNA-methylation profiling and AI and deep neural networks and got 99% accuracy," Klauschen said in a statement to Inside Digital Health . "Before our method, this was more less guess work."

It is good to see government-commissioned research echoing our warning about the dangers of police forces innovating in silos to manage the vast quantities of data they hold ("Police fear use of AI may lead to bias against disadvantaged", September 16). Our research shows a worrying lack of oversight or legal framework to mitigate some hefty risks -- of unlawful deployment, or of discrimination or bias that may be unwittingly built in. These dangers are exacerbated by a lack of transparency, central co-ordination or systematic knowledge-sharing between public bodies. Within the right framework algorithmic systems -- whether predictive policing, facial recognition technology or individual risk-assessment tools -- can deliver benefits in the justice system such as efficacy, efficiency, accountability and consistency. We need to build a consensus rooted in the rule of law, which preserves rights and equality, to deliver a trusted and reliable justice system now and for the future.

Recent efforts include working with government cyber-security agencies and insurance and financial industry experts to develop principles of responsible private sector response against attackers; collaborating with G-20 finance ministries and central banks, international financial institutions such as SWIFT, and global banks and insurers to develop practical norms to protect the integrity of financial data and transactions; initiatives in Silicon Valley and China to develop compatible approaches to promote Artificial Intelligence safety; and an effort to map how diverse stakeholders in China, India, and the United States assess risks associated with bioengineering techniques such as gene-editing.

The government's flagship National Leadership Centre has accepted its first cohort of officials from a spectrum of the public sector as part of moves to improve leadership across a host of services. The training academy is "a national offer for the most senior leaders of public services". The first of its kind in England, the programme will bring together leaders of public services to provide them coaching in areas including future technologies, like AI and robotics, to understand how they can both embrace new tools and collaborate to transform public service. The first cohort of invited participants includes police chief constables, fire service chiefs and hospital chief executives, who will begin to receive coaching from today. The aim of the scheme is to develop the skills of over 100 senior public service leaders every year, with the coaching programme developed with support from Oxford University and the Massachusetts Institute of Technology.

Many businesses are experimenting with artificial intelligence but lack an understanding of the use cases that deliver real business value. That's according to a new study from digital transformation firm Mindtree, which surveyed 650 global IT leaders on their use of AI in the workplace. It found that 85% of organizations have implemented a data strategy and 77% have invested in some AI-related technologies, with only 31% achieving a return on investment. The research shows that businesses can do more to gain increased value from their investments, although they need to focus on use cases that drive ROI. Suman Nambiar, head of strategy, partners and offering for digital at Mindtree, said: "Artificial Intelligence (AI) is transforming the way businesses across the world are operating, for instance, helping them deliver much more personalized experiences and services to their customers. "AI is delivering measurable business benefits to enterprises which experiment using agile, fast, value-driven innovation models, which can then be rolled out for wider use.

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and can be trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") are a core part of their business model and future success. Find all the details on our methodology here. The honorees span categories like human resources, security, insurance, and finance, with healthcare, transportation, and infrastructure startups best represented on the list.