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NinjaTech AI, a Silicon Valley-based generative AI company, has announced the public beta launch of its new AI Service Agent Ninja AI, a web application designed to act as a researcher, software engineer, planner/secretary and more. Users can now try it out for themselves at myninja.ai.
The service has a free tier and paid plans. For paying users, it provides access (via the application programming interfaces or APIs) to a number of leading generative AI models, including OpenAI's GPT-4o, Anthropic's Claude 3, and Google Gemini.
Users can choose between these AI models to perform a number of underlying operations simply by typing in natural language into Ninja AI, including web search, a 'deep search' performed by a more thorough AI agent, powered by Llama 3.
It can compare results from multiple AI models in real time using GPT-4 (summarizing the similarities and highlighting the differences), scheduling calendar events on behalf of the human user, and avoiding conflicts (this requires logging in with one's Google account for Google Calendar required, and an Apple iCal integration is also on the roadmap for the near future).
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It can further autonomously email invitations to human recipients (the agent can do this themselves from their own email address), talk to the user through different voices, and even video chat with them using Unreal Engine-powered 3D characters.
And Ninja AI can perform many of these tasks simultaneously and asynchronously, in the background while the user performs other tasks with Ninja AI or elsewhere on their devices.
The service pings them when an operation is completed, and users can check in to each workflow by clicking on a sidebar. Furthermore, unlike ChatGPT and other more consumer-oriented AI chabots, the user can type multiple requests into Ninja AI at once and it will attempt to do them all in the order the user requests them.
“Not everything is about question and answer,” said Babak Pahlavan, founder and CEO of NinjaTech AI, in a video chat interview with VentureBeat. “Especially in the real world, you need human assistants to interact with software, but also with other people.”
The five main agents that Ninja AI currently offers include:
- Ninja Advisor
- Ninja coder
- Basic planner
- Real-time Internet search
- Limited third party LLM access
Paid levels offer more tasks
Ninja AI is designed to have a “generous” free option, in Pahlavan's words, offering users up to 20 tasks daily from the Advisor, Coder, Researcher, and third-party LLMs, as well as 5 tasks per day from the Scheduler— agent
But users who want to pay €10, €20 or €30 monthly can do many more tasks daily and monthly.
Pahlavan previously spent more than a decade at Google, concluding his time there in 2022 as Senior Director of Product Management after overseeing several enterprise software verticals.
“My insight was that we needed something beyond question and answer systems, as smart as they are,” Pahlavan told VentureBeat. “And we almost did it within Google.”
After leaving the search giant, he joined the nonprofit scientific research group SRI International as an entrepreneur in residence, where the seeds of NinjaTech AI and Ninja AI were planted.
Pahlavan's co-founders include Sam Naghshineh, formerly a hyperscale systems engineer at Meta, who now serves as NinjaTech's Chief Technology Officer (CTO), and Arash Sadrieh, a close friend of Pahlavan and former senior applied scientist at Amazon Web Services (AWS). who now serves as NinjaTech's Chief Science Officer.
“We're essentially bringing together everything we've learned from Google, AWS and Meta about building software systems at scale in a global setting,” Pahlavan said.
Ambitious goal to run multiple AI models under one roof
The aim is to provide a service for busy professional consumers (prosumers) to get the most out of AI now, without waiting for a theoretical future breakthrough in the form of new models.
“The advisor agent is trained in thousands of human, multi-round conversations,” Pahlavan explains. “So it's meant to be thoughtful, friendly, clean, professional and suitable for work environments.”
Additionally: Ninja AI is designed to let users get the benefits of multiple AI models working together on their behalf under one virtual roof – without having to manually open and scroll through different models.
“The company's core competency is about agents being able to break down complex tasks, dynamically come up with a plan and then activate the tools at our disposal to execute those tasks, either in real time, asynchronously until the task is completed, or until it is blocked and there is a question for the user,” said Pahlavan.
Powered by AWS silicon
Interestingly, NinjaTech AI is eschewing the industry-leading generative AI chips – graphics processing units (GPUs) from Nvidia – in favor of custom machine learning chips from Amazon Web Services (AWS), manufactured by partner Taiwanese Semiconductor Manufacturing Company (TSMC).
NinjaTech used these chips, Trainium and Inferentia2, and Amazon's cloud-based machine learning service, Amazon SageMaker, to build, train, and scale its AI agents and enable them to perform multiple tasks simultaneously without the overhead costs. to boost young startups.
“We trained all the models with AWS Trainium through Sagemaker, and then everything is also controlled with Trainium and Inferentia,” says Pahlavan.
Rahul Kulkarni, Director of Product Management at AWS, commented on the benefits of the partnership in a video call with VentureBeat, highlighting that the custom silicon was supported and designed to work best with Amazon Sagemaker.
“Not only does it provide silicon, but it also provides the right framework in the software capabilities to ensure it can be used by companies like NinjaTech,” Kulkarni noted.
But how much cheaper are Inferentia2 chips than comparable Nvidia GPUs? AWS says customers can expect a 40% better price per equivalent performance – up to a point.
For super-demanding, compute-intensive operations, GPUs are still the way to go, and AWS also offers them through its Elastic Cloud (EC2) service.
“Our partnership with Nvidia continues to thrive and we will offer the most up-to-date infrastructure at scale,” said Kulkarni. “But just as important to us is our custom silicon initiative.”
With a team of experts from Google, AWS and Meta, NinjaTech AI aims to redefine productivity by allowing users to delegate time-consuming tasks to their AI agents, allowing them to focus on more strategic activities.