Google Translate to add real-time transcription feature

Google Translate will get a new feature before long that will enable it to translate people’s speech into another language and then transcribe it in real time.

“Your mobile phone effectively turns into a language translator for long-form speech,” Sami Iqran (pictured), product manager for Google Translate, told SiliconANGLE in an interview at a press event Wednesday in San Francisco.

The new feature is currently still under development, but Google officials said they hope to make it available to Android device users in a few months. Iqran said Google still needs to iron out some issues, in particular filtering out noise to make the translation work better.

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Verbit To Grow AI-Based Transcription Platform With New Funding Round

Verbit recently announced it raised $31 million in a Series B round of funding. This round of funding was led by Stripes and with participation from Viola Ventures, Vertex Ventures, HV Ventures, Oryzn Capital, and ClalTech.

This round of funding brings Verbit’s total amount raised to $65 million following a $23 million Series A round of funding in January 2019. Since then, the company’s valuation doubled and revenue tripled.

With this round of funding, the company is going to further accelerate its rapid growth, including expanding to new industry verticals, increasing the number of languages available, and innovating its speech recognition technology to make Verbit the go-to solution for artificial intelligence transcription.

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Want To Be AI-First? You Need To Be Data-First

Those that implement AI and Machine Learning project learn quickly that machine learning projects are not application development projects. Much of the value of machine learning projects rest in the models, training data, and configuration information that guides how the model is applied to the specific machine learning problem. The application code is mostly a means to implement the machine learning algorithms and "operationalize" the machine learning model in a production environment.  

Credit: Getty Images

That's not to say that application code is not necessary — after all, the computer needs some way to operationalize the machine learning model — but focusing a machine learning project on the application code is missing the big picture. If you want to be AI-first for your project, you need to have a data-first perspective.

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How to make the dreaded task of data entry less despised

A recent study showing that data entry is one the most redundant and hated workplace tasks raises questions about why, in the age of artificial intelligence, data mining and smart technologies, this task is still being done manually.

Is there any way it could be less despised? My ongoing fieldwork in a data-driven startup, referred to as Sage (a real company, but not its real name due to confidentiality requirements), suggests that technological solutions are not nearly as sophisticated as many assume — and are not going to replace human data entry any time soon.

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I Know Some Algorithms Are Biased—because I Created One

Artificial intelligence and machine learning are becoming common in research and everyday life, raising concerns about how these algorithms work and the predictions they make. For example, when Apple released its credit card over the summer, there were claims that women were given a lower credit limit than otherwise identical men were. In response, Sen. Elizabeth Warren warned that women “might have been discriminated against, on an unknown algorithm.”

On its face, her statement appears to contradict the way algorithms work. Algorithms are logical mathematical functions and processes, so how can they discriminate against a person or a certain demographic?

Credit: Getty Images

Creating an algorithm that discriminates or shows bias isn’t as hard as it might seem, however. As a first-year graduate student, my advisor asked me to create a machine-learning algorithm to analyze a survey sent to United States physics instructors about teaching computer programming in their courses. While programming is an essential skill for physicists, many undergraduate physics programs do not offer programming courses, leaving individual instructors to decide whether to teach programming.

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How Traditional Companies Can Utilize AI And Machine Learning To Build Better Products

Have you ever noticed how accurate Netflix's recommendations are to your taste? And how is Google Maps so confident I’m going home, that it will suggest directions to my house? Even my iPhone suggests what time I should set my alarm clock right before I go to bed. This means it knows when I’m going to bed and tells me the optimal time to wake up, down to the minute, based on my sleep patterns. Amazing, right?

So why do most organizations continue to use their data the same way they would have used it 10, 15 or even 20 years ago? Wouldn’t it make sense for businesses to use this technology to create better customer experiences and operational improvements?

Credit: Getty Images

What if you could use this technology to help your customers improve their lives? The good news is that the same machine learning technologies utilized within these large organizations are offered to the general public by various providers, such as AWS, Google Cloud Platform and Azure — for a fee, of course.

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