IBM to Launch Neural Network Learning Control Service

Developers believe that new service will bring greater transparency to the reasons for the decisions made by AI and can eliminate the "black box problem"
20 September 2018   1490

IBM has developed a service for monitoring the processes that occur during the training of neural networks. The system identifies emerging misconceptions and gives greater transparency to the reasons for the decisions made by AI.

The new tool works with popular AI-frameworks, such as Watson, Tensorflow, SparkML, AWS SageMaker and AzureML. The service is implemented on the IBM Cloud platform and will help monitor the learning process by making the necessary adjustments. According to the representatives of the company, the software is easy to adapt to any architecture of the neural network. Moreover, the system is able to automatically offer correction of input data to eliminate delusions.

The service shows the parameters of the learning process using visual diagrams, which makes the user's work easier. Among the data displayed is a combination of factors accepted for consideration, confidence in the decision made and the foundation of this confidence. In addition, changes to the parameters are stored in the log, which will allow you to study the actions of AI more closely.

The monitoring service is not free, but at the same time IBM said it plans to release an open source version of the product. The company declares this as a contribution to international cooperation in eliminating AI's misconceptions.

The reasons for the decisions made by artificial intelligence are in most cases hidden from the end user. At the same time, studies have shown that neural networks are able to assimilate inherent misconceptions and stereotypes, for example, gender or racial. This gave rise to some mistrust of AI and the fear of losing control over the technology. According to an IBM poll, 82% of entrepreneurs consider the introduction of neural networks. However, while 60% are afraid of possible problems, and 63% are not sure that they will be able to confidently manage new tools.

The so-called "black box problem", consisting in the non-transparency of AI decisions, is taken seriously by the world community. Work to increase transparency and trust is being carried out quite actively. In September 2018, MIT scientists published their development, illustrating the decision-making process by the neural network.

BNC to Monitor BTC Community's Mood

The system called Twitter Sentiment analyzes over 34M BTC-related Twitter posts each week, using AI to track the mood of the community
22 January 2020   209

Blockchain-based New Zealand-based research firm Brave New Coin (BNC) has unveiled a new system for measuring the mood of the Bitcoin community based on Twitter messages.

According to BNC, the new Twitter Sentiment rating system analyzes over 34 million BTC-related Twitter posts each week. The company uses artificial intelligence (AI) algorithms that look for records containing the words bitcoin, $ BTC and BTC and others.

BNC notes that user sentiment continues to be a “significant” factor in the price and dynamics of digital assets, and a new technique has been developed to track these sentiments. According to the BNC, it took 18 months to launch the Bitcoin Twitter Sentiment. The data obtained is divided into seven categories - Opinion, Technical Information, Inside the Network, Advertising, Bots, Macros and Hacking.

For the week ending January 17, the most common entries were in the Opinion category - their number was 30.42% of all data received. In second place was the category Technical Information, and in third inside the network (includes information on mining and hashrate).

BNC spokeswoman Pierre Ansaldi said that during the first quarter of this year, the company will also launch community sentiment analysis tools for other crypto assets.