Google is making it easier for companies to take advantage of the machine learning (ML) revolution with an offering that allows creation of custom machine learning models. The company on Wednesday showed off its new AI product that it is making available to folks outside of the Internet giant. With machine learning, applications are able to learn or adjust on their own without help from human developers. According to Tech Crunch, the search giant's chairman, Eric Schmidt said that Google believes machine learning is "what's next." With the new cloud service, the Internet giant will make it easier to employ some of the machine learning tech the company already uses to power features like Smart Reply in Inbox.

Cambridge Science Festival 2016 was the biggest and best ever, organisers have revealed. More than 350 events were held during the fortnight-long festival, attracting 60,000 visitors. Cambridge University, which runs the events, said the festival's main theme, artificial intelligence, sparked "considerable interest". This year was the 22nd in the festival's history, and it finished last Sunday with dozens of events on the Cambridge Biomedical Campus. A spokeswoman said: "We had two momentous weeks of over 350 events and 60,000 visits, making it the largest festival to date in terms of both events and visits. "This year was marked by the considerable interest from both the public and the media in many of the artificial intelligence and machine learning events, testament to both the fascination and the concern we all feel with our growing interaction and reliance on machines.

Data scientists often spend hours or days tuning models to get the highest accuracy. This tuning typically involves running a large number of independent Machine Learning (ML) tasks coded in Python or R. Following some work presented at Spark Summit Europe 2015, we are excited to release Scikit-learn integration package for Spark that dramatically simplifies the life of data scientists using Python. Python is one of the most popular programming languages for data exploration and data science, and this is in no small part due to high quality libraries such as Pandas for data exploration or scikit-learn for machine learning. Scikit-learn provides fast and robust implementations of standard ML algorithms such as clustering, classification, and regression. Scikit-learn's strength has typically been in the realm of computing on a single node, though.

Azure Machine Learning is Microsoft's machine learning studio. It provides a workbench for analysts to perform data analysis including applying predictive analytics and machine learning algorithms. One of the key uses of Machine Learning is finding correlations in data and using the relationships between different indicators to provide predictive power. Here is an example scenario I built in Azure ML. I found a dataset that describes a set of Community Health Status Indicators by county for the United States.

It's well understood that machine learning is eating the software world, so it's no surprise to see tech startups like Cosmify and LodgIQ emerging from stealth today with plans to leverage big unstructured data for a competitive advantage. San Francisco-based Cosmify came out of stealth today with a new solution that uses machine learning to jumpstart knowledge discovery across a range of information sources. The company's solution is designed to scan, analyze, and visualize unstructured data sources, such as documents, tweets, user data, chat logs, and photographs. Machine learning algorithms create a model of the data sources, and then maps all relevant relationships between them based on individual words or properties, according to Cosmify. Users can then explore the model to find outliers, discover behavioral trends, and predict future results.

Google is hoping to push machine learning as a mainstream business tool, with today's release of a set of preview products that take advantage of its cloud platform. Cloud Machine Learning relies on the open-source TensorFlow library, released late last year. Google said developers can use the company's tools such as Cloud Dataflow, BigQuery, Cloud Dataproc, Cloud Storage and Datalab, to train its machine learning. However, it is also offering pre-trained machine learning models with application programming interfaces. The company has been able to leverage large amounts of user and customer data stored in the applications it offers for the pre-trained models.

The United Nations Children's Fund, perhaps better known as UNICEF, has recently launched a new initiative through which they will begin to invest more money into technology start-ups that have the potential to better the lives of disadvantaged and vulnerable children all over the world. The new initiative, called Innovation Fund, has put a special focus on certain technologies that have the potential to help children, which include 3D printing, blockchain, wearables and sensors, artificial intelligence, and renewable energy. UNICEF, the United Nations program that has as its mandate the promotion of children's rights all over the world, has through its Innovation initiative put its focus on progessive projects and ideas that have the potential to help their cause. As stated on their website, UNICEF Innovation is "tasked with identifying, prototyping, and scaling technologies and practices that strengthen UNICEF's work." UNICEF is currently accepting submissions from various start-ups until February 26, 2016 through their website, though there are some requirements for being considered for funding.

Maybe the machines won't take over, but Eric Schmidt, chairman of Google parent company Alphabet, thinks machine learning might. The combination of cloud, crowdsourced information, and machine learning "will be the basis for every fundamental and hugely successful IPO win in the next five years," he said during this morning's keynote at GCP NEXT, the developer conference for Google Cloud Platform. Schmidt is prone to sweeping statements. But having watched computing transform many times in 45 years -- he was a Sun Microsystems bigwig when the company launched Java -- he said he felt qualified to predict that machine learning could lead to truly new innovations, the kind that can't yet be envisioned. Google is now offering the technology to cloud customers in the form of Cloud Machine Learning, an alpha application launched today.

Tay is an artificial intelligent chat bot developed by Microsoft's Technology and Research and Bing teams to experiment with and conduct research on conversational understanding. Tay is designed to engage and entertain people where they connect with each other online through casual and playful conversation. The more you chat with Tay the smarter she gets, so the experience can be more personalized for you. Tay may use the data that you provide to search on your behalf. Tay may also use information you share with her to create a simple profile to personalize your experience.

As artificial intelligence (AI) technologies such as the Amazon Echo and self-driving cars are hitting the market, they are poised to become an essential part of society. For people around the world, especially college students, this could mean some big changes. Once created, an AI can be used either internally or externally. Internal interfaces are located on a cloud and can access other devices and software that is used in the home such as a TV or smartphone. Technology like the Amazon Echo, which can access apps that are downloaded on a smart phone, is an example of this, but in comparison this technology is rudimentary compared to what others have developed.