Goto

Collaborating Authors

Representation & Reasoning


Amazon's Alexa being tested to replicate voice of dead relatives

#artificialintelligence

Amazon's Alexa might soon replicate the voice of family members - even if they're dead. The capability, unveiled at Amazon's Re:Mars conference in Las Vegas, is in development and would allow the virtual assistant to mimic the voice of a specific person based on a less than a minute of provided recording. Rohit Prasad, senior vice president and head scientist for Alexa, said at the event Wednesday that the desire behind the feature was to build greater trust in the interactions users have with Alexa by putting more "human attributes of empathy and affect." "These attributes have become even more important during the ongoing pandemic when so many of us have lost ones that we love," Prasad said. "While AI can't eliminate that pain of loss, it can definitely make their memories last."


The Emergence of the Composable Buyer Information Platform - Channel969

#artificialintelligence

This can be a collaborative put up between Databricks, Hightouch, and Snowplow. We thank Martin Lepka (Head of Business Options at Snowplow) and Alec Haase (Product Evangelist at Hightouch) for his or her contributions. There isn't any denying that one of many best belongings to the trendy digital group is first-party buyer information. The fast rise of the privacy-centric client has led to a monumental shift away from third-party monitoring strategies. Organizations are actually scrambling to implement a knowledge infrastructure that, leveraging first-party information, can allow the customized experiences that clients count on with each interplay.


The Impact of AI on Healthcare: How to Make the Models Work?

#artificialintelligence

Research into Artificial Intelligence (AI) has been ongoing for decades, with early proposals dating back to 1950. However, only in recent years, it has seen a resurgence in popularity thanks to the increased availability of computing power and the growth of big data and machine learning. AI is the ability of machines to perform tasks that ordinarily require human intelligence, such as understanding natural language and recognizing objects. With the rapid expansion of AI, there are opportunities for businesses and individuals alike to capitalize on its capabilities. AI is a field of computer science and engineering focused on the creation of intelligent agents, which are systems that can reason, learn, and act autonomously.


IBM Data Engineering

#artificialintelligence

This Professional Certificate is for anyone who wants to develop job-ready skills, tools, and a portfolio for an entry-level data engineer position. Throughout the self-paced online courses, you will immerse yourself in the role of a data engineer and acquire the essential skills you need to work with a range of tools and databases to design, deploy, and manage structured and unstructured data. By the end of this Professional Certificate, you will be able to explain and perform the key tasks required in a data engineering role. You will use the Python programming language and Linux/UNIX shell scripts to extract, transform and load (ETL) data. You will work with Relational Databases (RDBMS) and query data using SQL statements.


Kinetic Component Analysis

#artificialintelligence

We introduce Kinetic Component Analysis (KCA), a state-space application that extracts the signal from a series of noisy measurements by applying a Kalman Filter on a Taylor expansion of a stochastic process. We show that KCA presents several advantages compared to other popular noise-reduction methods such as Fast Fourier Transform (FFT) or Locally Weighted Scatterplot Smoothing (LOWESS): First, KCA provides band estimates in addition to point estimates. Second, KCA further decomposes the signal in terms of three hidden components, which can be intuitively associated with position, velocity and acceleration. Third, KCA is more robust in forecasting applications. Fourth, KCA is a forward-looking state-space approach, resilient to structural changes.


Amazon's Alexa could soon speak in a dead relative's voice

NPR Technology

Do you miss the sound of a dead relative's voice? Well fear not: Amazon unveiled a new feature in the works for its virtual assistant Alexa that can read aloud in a deceased loved one's voice based on a short recording of the person. "While AI can't eliminate that pain of loss, it can definitely make their memories last," said Rohit Prasad, senior vice president and head scientist for Alexa, on Wednesday at Amazon's re:MARS conference in Las Vegas. In a video played at the event, an Amazon Echo Dot is asked: "Alexa, can Grandma finish reading me'The Wizard of Oz'?" "Instead of Alexa's voice reading the book, it's the kid's grandma's voice," Prasad said. "We had to learn to produce a high quality voice with less than a minute of recording."


Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery

#artificialintelligence

This paper revisits datasets and evaluation criteria for Symbolic Regression, a task of expressing given data using mathematical equations, specifically focused on its potential for scientific discovery. Focused on a set of formulas used in the existing datasets based on Feynman Lectures on Physics, we recreate 120 datasets to discuss the performance of symbolic regression for scientific discovery (SRSD). For each of the 120 SRSD datasets, we carefully review the properties of the formula and its variables to design reasonably realistic sampling range of values so that our new SRSD datasets can be used for evaluating the potential of SRSD such as whether or not an SR method con (re)discover physical laws from such datasets. As an evaluation metric, we also propose to use normalized edit distances between a predicted equation and the ground-truth equation trees. While existing metrics are either binary or errors between the target values and an SR model's predicted values for a given input, normalized edit distances evaluate a sort of similarity between the ground-truth and predicted equation trees.


AI-powered legal ediscovery helps dig through data at scale

#artificialintelligence

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. If there is one thing common to all legal cases, it is documents. In decades past, the evidence collected in litigation was often confined to digging through folders and filing cabinets, in a process called discovery. Today, electronic discovery, or'ediscovery,' is the name of the game – with paper documents replaced by millions of emails, Slack messages and Zoom calls. MarketsandMarkets estimates the global ediscovery market size to grow from $9.3 billion in 2020 to $12.9 billion by 2025.


AI: The emerging Artificial General Intelligence debate

#artificialintelligence

Since Google's artificial intelligence (AI) subsidiary DeepMind published a paper a few weeks ago describing a generalist agent they call Gato (which can perform various tasks using the same trained model) and claimed that artificial general intelligence (AGI) can be achieved just via sheer scaling, a heated debate has ensued within the AI community. While it may seem somewhat academic, the reality is that if AGI is just around the corner, our society--including our laws, regulations, and economic models--is not ready for it. Indeed, thanks to the same trained model, generalist agent Gato is capable of playing Atari, captioning images, chatting, or stacking blocks with a real robot arm. It can also decide, based on its context, whether to output text, join torques, button presses, or other tokens. As such, it does seem a much more versatile AI model than the popular GPT-3, DALL-E 2, PaLM, or Flamingo, which are becoming extremely good at very narrow specific tasks, such as natural language writing, language understanding, or creating images from descriptions.


New Amazon Alexa feature will creepily mimic dead loved one's voices

Mashable

Your dead loved ones are never really gone, they're just trapped inside Amazon's voice-assisted devices. Wednesday, at Amazon's conference re:MARS (machine learning, automation, robotics, and space) Rohit Prasad, SVP and head scientist of Alexa AI announced Alexa's new supernatural talent: the ability to mimic someone's voice using less than a minute of recording. A spokesperson said in an email this is something Amazon has been exploring based on recent advancements in TTS (text-to-speech) technology. Amazon didn't have a specific timeline to share, only that is it something it is currently working on. Prasad described the voices of dead loved ones as a primary use case for this feature citing attributes of empathy and affect as keys to building trust with a companion, in this case, an AI-powered device.