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IonQ Announces 2 New Quantum Systems; Suggests Quantum Advantage is Nearing

It’s been a busy week for IonQ, the quantum computing start-up focused on developing trapped-ion-based systems. At the Quantum World Congress today, the company announced two new systems (Forte Enterprise and Tempo) intended to be rack-mountable and deployable in a traditional data center. Yesterday, speaking at Tabor Communications (HPCwire parent organization) HPC and AI on Wall Street conference, the company made a strong pitch for reaching quantum advantage in 2–3 years, using the new systems.

If you’ve been following quantum computing, you probably know that deploying quantum computers in the datacenter is a rare occurrence. Access to the vast majority NISQ era computers has been through web portals. The latest announcement from IonQ, along with somewhat similar announcement from neutral atom specialist QuEra in August, and increased IBM efforts (Cleveland Clinic and PINQ2) to selectively place on-premise quantum systems suggest change is coming to the market.

IonQ’s two rack-mounted solutions are designed for businesses and governments wanting to integrate quantum capabilities within their existing infrastructure. “Businesses will be able to harness the power of quantum directly from their own data centers, making the technology significantly more accessible and easy to apply to key workflows and business processes,” reported the company. IonQ is calling the new systems enterprise-grade. (see the official announcement.)

GPT-4 “crushes” other LLMs according to new benchmark suite

Benchmarks are a key driver of progress in AI. But they also have many shortcomings. The new GPT-Fathom benchmark suite aims to reduce some of these pitfalls.

Benchmarks allow AI developers to measure the performance of their models on a variety of tasks. In the case of language models, for example, answering knowledge questions or solving logic tasks. Depending on its performance, the model receives a score that can then be compared with the results of other models.

These benchmarking results form the basis for further research decisions and, ultimately, investments. They also provide information about the strengths and weaknesses of individual methods.

Scaling up learning across many different robot types

Robots are great specialists, but poor generalists. Typically, you have to train a model for each task, robot, and environment. Changing a single variable often requires starting from scratch. But what if we could combine the knowledge across robotics and create a way to train a general-purpose robot?

Today, we are launching a new set of resources for general-purpose robotics learning across different robot types, or embodiments. Together with partners from 33 academic labs we have pooled data from 22 different robot types to create the Open X-Embodiment dataset. We also release RT-1-X, a robotics transformer (RT) model derived from RT-1 and trained on our dataset, that shows skills transfer across many robot embodiments.

In this work, we show training a single model on data from multiple embodiments leads to significantly better performance across many robots than those trained on data from individual embodiments. We tested our RT-1-X model in five different research labs, demonstrating 50% success rate improvement on average across five different commonly used robots compared to methods developed independently and specifically for each robot. We also showed that training our visual language action model, RT-2, on data from multiple embodiments tripled its performance on real-world robotic skills.

Why Big Tech’s bet on AI assistants is so risky

This is a risky bet, given the limitations of the technology. Tech companies have not solved some of the persistent problems with AI language models, such as their propensity to make things up or “hallucinate.” But what concerns me the most is that they are a security and privacy disaster, as I wrote earlier this year. Tech companies are putting this deeply flawed tech in the hands of millions of people and allowing AI models access to sensitive information such as their emails, calendars, and private messages. In doing so, they are making us all vulnerable to scams, phishing, and hacks on a massive scale.

I’ve covered the significant security problems with AI language models before. Now that AI assistants have access to personal information and can simultaneously browse the web, they are particularly prone to a type of attack called indirect prompt injection. It’s ridiculously easy to execute, and there is no known fix.

In an indirect prompt injection attack, a third party “alters a website by adding hidden text that is meant to change the AI’s behavior,” as I wrote in April. “Attackers could use social media or email to direct users to websites with these secret prompts. Once that happens, the AI system could be manipulated to let the attacker try to extract people’s credit card information, for example.” With this new generation of AI models plugged into social media and emails, the opportunities for hackers are endless.

AI is coming to the Arc browser — but probably not like you think

Sure, you could just stick a ChatGPT sidebar in your browser. But what do we really want AI to do for us as we use the web? That’s the much harder question.

At some point, if you’re a company doing pretty much anything in the year 2023, you have to have an AI strategy. It’s just business. You can make a ChatGPT plug-in. You can do a sidebar. You can bet your entire trillion-dollar company on AI being the future of how everyone does everything. But you have to do something.

The last one of these was crypto and the blockchain a couple of years ago, and Josh Miller, the CEO of The Browser Company, which makes the popular new Arc browser, says he’s… More.


AI is coming for your online life… but nobody’s exactly sure how it’s going to work.

Zoom Docs launches in 2024 with built-in AI collaboration features

Zoom’s selling a cheaper AI package than Microsoft 365 Copilot and Google Duet AI, and soon it can plug into a new ‘modular workspace.’

At Zoomtopia 2023 today, Zoom announced Zoom Docs, a collaboration-focused “modular workspace” that integrates the company’s Zoom AI Companion for generating new content or populating a doc from other sources — you know the drill by now.

Along with the Mail and Calendar offerings launched during last year’s event, Zoom Docs is another step toward a full office suite alternative to Google Workspace and Microsoft 365, which both have started to integrate AI-powered tools of their own, dubbed Duet AI and Copilot, respectively. The company says it will be widely… More.


Zoom’s new tool expands beyond the Zoom meeting.

Oracle Doubles Down On Generative AI Trend At CloudWorld 2023

Last week at its annual CloudWorld event in Las Vegas, Oracle showed that it, too, is going full throttle on generative AI–and that it has no plans to cower to its biggest rival Amazon Web Services (AWS.)Before we get into the CloudWorld event itself, it’s important to take a tiny step back to September 14 when the company announced a new partnership with Microsoft that puts Oracle database services on Oracle Cloud Infrastructure (OCI) in Microsoft Azure. The new Oracle Database@Azure makes Microsoft and Oracle the only two hyperscalers to offer OCI to help simplify cloud migration, deployment and management. Especially when you consider that the partners have achieved rate card and… More.


This year at Oracle CloudWorld, the company advanced its generative AI strategy across its cloud infrastructure, apps, and platforms. Exploring this year’s announcements.

New AI model can tell if you need lung cancer screening

Lung cancer screening is crucial for decreasing the death count from the disease but the government can’t scan everyone’s lungs. Here is an AI that identifies people who actually need screening.

Lung cancer is the deadliest cancer type, killing over a million people annually across the globe. The disease is responsible for the highest number of cancer deaths in both men and women in the US.

In fact, the death toll from lung cancer among women and men is nearly triple that of breast cancer and prostate cancer, respectively.