Nvidia’s new AI platforms, AI processors by Ceva, a new platform for many agent reinforcement learning, and more in today’s top stories around artificial intelligence, blockchain, and data science news.
1. Ethereum Foundation is looking for outside developers to help them solve Blockchain’s scaling problem
Ethereum creators are exploring newer ways to fix the inability of blockchains to effectively scale. They are inviting outside developers to help solve the scaling problem. Until now, Ethereum has explored two possible fixes for the problem. The first solution is sharding which would require a small percentage of nodes to see and process every transaction, allowing many more transactions to be processed in parallel at the same time.
The second solution involves creating data-link layers or layer 2 protocols that send most transactions off-chain and only interact with the underlying blockchain in order to enter and exit from the layer-2 system or in case of attacks on the system.
A specification for an initial prototype is close to finalized and the next step involves building a reference implementation in python on top of Py-EVM, and a testnet in python. Outside developers are now invited to get involved in this sharding testnet and then the sharding mainnet steps. Ethereum is offering subsidies ranging from $50,000 to $1 million to programmers who can help find the fixes. Interested developers can send their proposals to email@example.com. For more information visit here.
At the ongoing CES 2018, Nvidia has announced three new variants of its DRIVE AI platform, which are based around Xavier SoCs. The Xavier autonomous machine intelligence processors are now shipping out to customers, after being unveiled last year.
Most of Nvidia’s initiatives, this year, revolve around self-driving cars and its platform for allowing car manufacturers to build their own.
DRIVE AR, the first of the DRIVE AI offerings, aims at enhancing and transforming the driving experience by adding augmented reality into vehicles leveraging computer vision, graphics, and artificial intelligence capabilities.
DRIVE IX, the second platform, helps developers build and deploy in-car AI assistants. These AI assistants will interact with drivers as well as passengers on the road by incorporating both interior and exterior sensor data.
Apart, from these, Nvidia has launched a revision of Pegasus, it’s autonomous taxi brain. According to them, “it delivers the performance of a trunk full of PCs in an auto-grade form factor the size of a license plate” Nvidia is currently working with at least 25 customers using Pegasus to power their self-driving robotaxi fleet.
Volkswagen joins forces with Nvidia to use it’s Drive IX platform in some of its upcoming vehicles, including the I.D. Buzz electric bus. Drive IX, announced at CES 2018, is a software developer kit that Nvidia created to tap into the power of Xavier. Volkswagen will use it to build features like facial recognition, gesture control, natural language processing, and more in their microbus. Volkswagen will initially focus on building Intelligent Co-Pilot features and using sensor data to make driving easier, safer and more convenient for drivers. Volkswagen will also work with Drive AR, a new augmented reality-based SDK from Nvidia to incorporate augmented reality into vehicles. The partnership between the two companies is also likely to be extended to future vehicles.
MAgent is a new platform to support research and development of many agent reinforcement learning. Instead of using single or multi-agent reinforcement learning, MAgent focuses on supporting the tasks and the applications that require hundreds to millions of agents.
Within the interactions among a population of agents, it enables not only the study of learning algorithms for agents’ optimal policies but more importantly, the observation and understanding of individual agent’s behaviors and social phenomena emerging from the AI society, including communication languages, leadership, altruism.
MAgent is highly scalable and can host up to one million agents on a single GPU server. MAgent also provides flexible configurations for AI researchers to design their customized environments and agents. You can read the AAAI 2018 demo paper here. You can also watch the demo video for some interesting showcases here.
Ceva Inc has unveiled NeuPro, an AI processor family for deep learning inference at the edge, at the CES 2018. It is designed for edge device vendors looking to quickly take advantage of the significant possibilities that deep neural network technologies offer. The AI processors offer performance ranging from 2 Tera Ops Per Second (TOPS) for the entry-level processor and 12.5 TOPS for the most advanced configuration. The NeuPro processor line extends the use of AI to new edge-based applications such as natural language processing, real-time translation, authentication, workflow management, etc.
The NeuPro family comprises four AI processors offering different levels of parallel processing:
- NP500 the smallest processor, targeting IoT, wearables, and cameras.
- NP1000 targeting mid-range smartphones, ADAS, industrial applications and AR/ VR headsets.
- NP2000 for high-end smartphones, surveillance, robots, and drones.
- NP4000 for high-performance edge processing in enterprise surveillance and autonomous driving.