Algorithms that produce artistic pieces like musical compositions, film scripts, and book plots are a sophisticated piece of technology for they need to understand the concepts that are even difficult for humans to explain. Google has launched the Magenta Project, aimed towards the development of AI and machine learning tools for arts and music.
The Magenta Project will be driven by the TensorFlow, which is a library containing various machine learning tools. Google recently released TensorFlow as an open source tech.
TensorFlow-A Library of ML Tools
TensorFlow comprises of machine learning tools to perform complex tasks like identifying audio and visual signals or read a text and extract meaning from it. These tools allow the developers to come up with highly intelligent products.
Given that the human knowledge is very complex, it is impossible for it to be pre-programmed using a set of logics. This shortcoming of rule-based systems is owing to the fact that human intelligence is too intricate and complicated to be replicated.
TensorFlow has overcome this problem by adopting the learning approach. The AI system learns on the go and Google has open sourced the technology for algorithm training. This has opened the gateways for the developers to get to interact with the machines and come up with stronger apps, even if their knowledge of AI is quite limited.
Open Sourcing the TensorFlow
One might question Google’s intention behind open sourcing valuable piece of technology like TensorFlow. The decision to release the technology to the world was taken by Jeff Dean. Dean felt that the slow pace of progress was hampering the company’s efforts to make rapid advances in the field. He believed that the way forward was to involve more people and get their opinion about TensorFlow.
Now, the team does not have to wait until a conference to discuss its ideas; rather they could interact with the scientists across the world, as and when an issue pops up. Rajat Monga, the leader of the TensorFlow team, believes:
“Having this system open sourced we’re able to collaborate with many other researchers at universities and startups, which gives us new ideas about how we can advance our technology. Since we made the decision to open-source, the code runs faster, it can do more things and it’s more flexible and convenient.”
Value based Ecosystem drives the Open-source Trend
For the traditionalists, Google’s decision to open-source TensorFlow may seem absurd. Imagine MacDonald’s releasing its secret recipe for McChicken or Pepsi making its secret formula public! Even Apple is notorious about its secrecy rules for the unreleased products.
Albeit the severe competition in the technology arena, Facebook has announced that it will make its library of AI tools public. Similarly, IBM has distributed the quantum computing platform via cloud while Tesla released its electric car patents.
Even with the best minds on board, these companies need another set of eyes to examine their technologies and expand their reach. Unlike the conventional enterprise system, the advantage lies with the one who creates value for the entire ecosystem.