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A recent controversy has surfaced regarding AI with ties to government. A group of Google employees has urged Congress to adopt stronger whistleblower protections for employees. And a new report by the National Security Commission on Artificial Intelligence urges federal agencies to provide employees with reporting rights. In addition, the commission recommended that governments invest in democratizing AI and create an accredited university for AI talent.

Exposing weaknesses

While AI with ties to government agencies should be subject to scrutiny, some experts caution against relying on these reviews. In many cases, the ties between government agencies and AI vendors can compromise the integrity of these audits. For instance, the US government has commissioned an audit of a medical AI tool. Such third-party oversight is critical in exposing weaknesses in AI systems.

Third-party oversight of AI products has been a challenge, despite a number of accreditation schemes for third-party auditors. Because such third-party auditors have access to confidential information, ensuring the independence of these auditors is difficult. As a result, many audit schemes include post-audit actions to ensure independence.

Lack of transparency and access to data is a serious vulnerability in the current AI audit ecosystem. While protecting proprietary information is a necessary first step, it is not the appropriate response. While all audit systems grant privileged access to auditors, access to data is not required to be direct. In fact, the National Institute of Standards and Technology uses a custom API to protect its face recognition vendor test models.

Human trafficking

The use of AI for tax purposes should also be considered carefully. Moreover, governments should ensure that AI systems are properly governed. For example, AI is being used by governments to prevent money laundering, which can cut funding for narcotics, terrorism, and human trafficking.

If you’re looking for the top news on artificial intelligence, enterprise technologies, privacy, and blockchain, you’ve come to the right place. I’m Sage Lazzaro, a senior reporter at VentureBeat. I cover the latest in the industry and the companies that are making it happen.

Aquant is a software that mines data from various sources to produce actionable insights for your business. It works by learning the language of various companies’ service processes and extracting insights from data silos like customer relationship management platforms and enterprise resource planning software. The AI takes days to learn the language of a company and can mine data from millions of customer tickets, parts catalogs, inventory, supply chains, and even internet of things alerts.

Aquant raised an additional $30 million in a series B round. This represents the company’s second round of financing in 14 months. The company plans to use the money to expand its engineering, client services, and go-to-market teams. Increasing customer demands and expectations have created new challenges for service delivery.

Focusing on increasing
The new funding will help Quantum Metric expand its global footprint and continue its product development. The company is focusing on increasing headcount to 220 employees and expanding across the US and EMEA regions. It also plans to increase its technology investment, with more than a dozen open tech positions.

The company uses a continuous product design (CPD) methodology to help businesses build digital products faster. This philosophy, which draws upon the principles of agile design and development processes, focuses on increasing efficiency and adapting to change. The company’s CPD methodology allows businesses to develop innovative products based on data from their customers.

Quantum Metric’s platform automates website performance monitoring and reduces the time it takes to resolve a problem from days to minutes. It uses Google BigQuery to analyze petabytes of data to track key performance indicators. The data can be used to measure how much money a company loses each day due to poor website performance. For example, a slow page can cause customers to abandon the checkout process.

Company expand globally

The cybersecurity company Coalition has raised $175 million in new funding led by Index Ventures. The investment comes at a time when cyber attacks are on the rise. As a result, many companies are turning to remote work to prevent data breaches. The money will help the company expand globally.

Iterable is a cross-channel platform for customer experience management. It recently raised $200 million in Series E funding from investors including Glynn Capital, Silver Lake, Adams Street, and Deutsche Telekom Capital Partners. The company expects to use the funds for hiring, R&D, marketing, and geographic expansion.

The company’s AI-powered solutions are designed to enable marketers to better understand their customers. They provide insight into the customer behavior by analyzing their online interactions and customer feedback. These signals are then converted into affinity labels that marketers can use to develop and implement campaigns accordingly.

This pattern is also known as Gen Ju. It is a Chinese character that represents a person. It is composed of two iterations of a base function called gen. The initials j are used as a placeholder for the next iteration. The resulting function returns a value for each iteration.

Big data analytics

Iterable’s products are designed to improve the performance of cross-channel campaigns. Their products use big data analytics to analyze user behavior, optimize engagement time, and identify channels that convert. This enables every marketer to build meaningful relationships with their customers. The company’s mission is to make this possible by making cross-channel marketing a reality.

Noogata, founded by Assaf Egozi, is an AI startup that provides a platform with modular preset AI blocks. The company’s AI framework abstracts away most of the development work, allowing customers to quickly and easily deploy AI solutions that help companies make better decisions. Some of its customers include PepsiCo and Colgate-Palmolive Company.

Hugging Face, an artificial intelligence startup, has been awarded the VentureBeat Innovation in Natural Language Process/Understanding Award for 2021. Founded in 2016, Hugging Face has a community of over 100,000 members. This year, the company plans to triple its efforts. Not only will it expand to language translation, but it will also build a community where users can share their machine learning models.

Conclusion

Hugging Face is building software to analyze text. Its software is open source and able to handle a variety of NLP tasks. Additionally, the company is creating datasets, which are crucial to NLP. It also hosts a repository of pretrained NLP models on GitHub.

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