Competition in NLP (Natural Language Processing) is heating up. OpenAI is currently seen as the industry leader with its GPT-3 model but rivals are gaining traction.

Investors see AI21 Labs as one of the most promising contenders.

“We completed this round during a period of market uncertainty, which highlights the confidence our investors have in AI21’s vision to change the way people consume and produce information,” said Ori Goshen, Co-Founder and Co-CEO of AI21 Labs.

“The funding will allow us to accelerate the company’s global growth while continuing to develop advanced technology in the field of natural language processing. We are looking forward to growing our team and our offerings.”

The latest funding round was led by Ahren and brings AI21 Labs’ valuation to $664 million.

“NLP has reached a critical inflection point and AI21 has developed unique infrastructure and products to successfully serve a large and rapidly growing market” commented Alice Newcombe-Ellis, Founding and General Partner of Ahren.

“We consider this team to be of the highest calibre, both technically and commercially, leading a differentiated company in a transformative space.”

AI21 Labs’ Jurassic-1 Jumbo model is around the size of GPT-3. The company has been gradually building products around it, including its ‘AI-as-a-Service’ platform AI21 Studio.

One of the consumer-facing products launched by AI21 Labs is Wordtune, an AI writing tool with millions of active users that was chosen by Google as one of its favourite extensions for 2021.

Another product, Wordtune Read, is able to analyse and summarise documents in seconds—enabling users to read long and complex text quickly and efficiently.

A survey last year by John Snow Labs found that 60 percent of budgets for NLP technologies increased by at least 10 percent in 2020, while 33 percent reported a 30 percent increase and 15 percent said their budget more than doubled.

NLP specialists like AI21 Labs are set to benefit greatly from the clear appetite for such technologies over the coming years.

(Image Credit: AI21 Labs)

Related: Meta’s NLLB-200 AI model improves translation quality by 44%

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LinkedIn co-founder Reid Hoffman is joining Suleyman on the venture.

“Reid and I are excited to announce that we are co-founding a new company, Inflection AI,” wrote Suleyman in a statement.

“Inflection will be an AI-first consumer products company, incubated at Greylock, with all the advantages and expertise that come from being part of one of the most storied venture capital firms in the world.”

Dr Karén Simonyan, another former DeepMind AI expert, will serve as Inflection AI’s chief scientist and its third co-founder.

“Karén is one of the most accomplished deep learning leaders of his generation. He completed his PhD at Oxford, where he designed VGGNet and then sold his first company to DeepMind,” continued Suleyman.

“He created and led the deep learning scaling team and played a key role in such breakthroughs as AlphaZero, AlphaFold, WaveNet, and BigGAN.”

Inflection AI will focus on machine learning and natural language processing.

“Recent advances in artificial intelligence promise to fundamentally redefine human-machine interaction,” explains Suleyman.

“We will soon have the ability to relay our thoughts and ideas to computers using the same natural, conversational language we use to communicate with people. Over time these new language capabilities will revolutionise what it means to have a digital experience.”

Interest in natural language processing is surging. This month, Microsoft completed its $19.7 billion acquisition of Siri voice recognition engine creator Nuance.

Suleyman departed Google in January 2022 following an eight-year stint at the company.

While at Google, Suleyman was placed on administrative leave following bullying allegations. During a podcast, he said that he “really screwed up” and was “very sorry about the impact that caused people and the hurt people felt.”

Suleyman joined venture capital firm Greylock after leaving Google.

“There are few people who are as visionary, knowledgeable and connected across the vast artificial intelligence landscape as Mustafa,” wrote Hoffman, a Greylock partner, in a post at the time.

“Mustafa has spent years thinking about how technological advances impact society, and he cares deeply about the ethics and governance supporting new AI systems.”

Inflection AI was incubated by Greylock. Suleyman and Hoffman will both remain venture partners at the company.

Suleyman promises that more details about Inflection AI’s product plans will be provided over the coming months.

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The supercomputer is called the AI Research SuperCluster (RSC) and is yet to be fully complete. However, Meta’s researchers have already begun using it for training large natural language processing (NLP) and computer vision models.

RSC is set to be fully built in mid-2022. Meta says that it will be the fastest in the world once complete and the aim is for it to be capable of training models with trillions of parameters.

“We hope RSC will help us build entirely new AI systems that can, for example, power real-time voice translations to large groups of people, each speaking a different language, so they can seamlessly collaborate on a research project or play an AR game together,” wrote Meta in a blog post.

“Ultimately, the work done with RSC will pave the way toward building technologies for the next major computing platform — the metaverse, where AI-driven applications and products will play an important role.”

For production, Meta expects RSC will be 20x faster than Meta’s current V100-based clusters. RSC is also estimated to be 9x faster at running the NVIDIA Collective Communication Library (NCCL) and 3x faster at training large-scale NLP workflows.

A model with tens of billions of parameters can finish training in three weeks compared with nine weeks prior to RSC.

Meta says that its previous AI research infrastructure only leveraged open source and other publicly-available datasets. RSC was designed with the security and privacy controls in mind to allow Meta to use real-world examples from its production systems in production training.

What this means in practice is that Meta can use RSC to advance research for vital tasks such as identifying harmful content on its platforms—using real data from them.

“We believe this is the first time performance, reliability, security, and privacy have been tackled at such a scale,” says Meta.

(Image Credit: Meta)

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Watson Discovery is an AI-powered intelligent search and text-analytics platform that can retrieve critical information buried in enterprise data.

In one case study, Woodside Energy had no way to retrieve the 30 years’ worth of valuable engineering and drilling knowledge that was buried in unstructured documentation. Using the existing NLP capabilities of Watson Discovery, the firm reportedly cut research time by more than 75 percent.

Among the new enhancements planned for Watson Discovery are:

• Pre-trained document structure understanding: Watson Discovery’s Smart Document Understanding feature now includes a new pre-trained model designed to automatically understand the visual structure and layout of a document without additional training from a developer or data scientist.
• Automatic text pattern detection: A new advanced pattern creation feature is available in beta that helps users to quickly identify business-specific text patterns within their documents. It can start learning the underlying text patterns from as little as two examples and then refines the pattern based on user feedback.
• Advanced NLP customisation capabilities: With a new custom entity extractor feature, IBM is simplifying the process of training NLP models to identify highly-customised, business-specific words by reducing the data prep effort, simplifying labeling with active learning and bulk annotation capabilities, and enabling simple model deployment to accelerate training time.

“The stream of innovation coming to IBM Watson from IBM Research is why global businesses in the fields of financial services, insurance, and legal services turn to IBM to help detect emerging business trends, gain operational efficiency and empower their workers to uncover new insights,” said Daniel Hernandez, General Manager of Data and AI, IBM.

“The pipeline of natural language processing innovations we’re adding to Watson Discovery can continue to provide businesses with the capabilities to more easily extract the signal from the noise and better serve their customers and employees.”

(Image Credit: IBM)

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Dr Alex Young is a trained orthopaedic and trauma surgeon who founded Virti and set out to use emerging technologies to provide immersive training for both new healthcare professionals and experienced ones looking to hone their skills.

COVID-19 has put most in-person training on hold to minimise transmission risks. Hospitals and universities across the UK and US are now using the virtual patient as a replacement—including our fantastic local medics and surgeons at the Bristol NHS Foundation Trust.

The virtual patient uses Natural Language Processing (NLP) and ‘narrative branching’ to allow medics to roleplay lifelike clinical scenarios. Medics and trainees can interact with the virtual patient using their tablet, desktop, or even VR/AR headsets for a more immersive experience.

Dr Alex Young comments:

“We’ve been working with healthcare organisations for several years, but the pandemic has created really specific challenges that technology is helping to solve. It’s no longer safe or practicable to have 30 medics in a room with an actor, honing their clinical soft-skills. With our virtual patient technology, we’ve created an extremely realistic and repeatable experience that can provide feedback in real time. This means clinicians and students can continue to learn valuable skills.

Right now, communication with patients can be very difficult. There’s a lot of PPE involved and patients are often on their own. Having healthcare staff who are skilled in handling these situations can therefore make a huge difference to that patient’s experience.”

Some of the supported scenarios include: breaking bad news, comforting a patient in distress, and communicating effectively whilst their faces are obscured by PPE. Virti’s technology was also used at the peak of the pandemic to train NHS staff in key skills required on the front line, such as how to safely use PPE, how to navigate an unfamiliar intensive care ward, how to engage with patients and their families, and how to use a ventilator.

Tom Woollard, West Suffolk Hospital Clinical Skills and Simulation Tutor, who used the Virti platform at the peak of the COVID pandemic, comments:

“We’ve been using Virti’s technology in our intensive care unit to help train staff who have been drafted in to deal with COVID-19 demand.

The videos which we have created and uploaded are being accessed on the Virti platform by nursing staff, physiotherapists and Operational Department Practitioners (ODPs) to orient them in the new environment and reduce their anxiety.

The tech has helped us to reach a large audience and deliver formerly labour-intensive training and teaching which is now impossible with social distancing.

In the future, West Suffolk will consider applying Virti tech to other areas of hospital practice.”

The use of speech recognition, NLP, and ‘narrative branching’ provides a realistic simulation of how a patient would likely respond—providing lifelike responses in speech, body language, and mannerisms.

The AI delivers real-time feedback to the user so they can learn and improve. With upwards of 70 percent of complaints against health professionals and care providers attributable to poor communication, the virtual patient could help to deliver better care while reducing time spent handling complaints.

Virti’s groundbreaking technology has – quite rightly – been named one of TIME’s best inventions of 2020.

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The consortium includes Google DeepMind, Facebook AI, New York University, and the University of Washington. Each of the consortium’s members believe a more comprehensive benchmark is needed for NLP than current solutions.

The result is a benchmarking platform called SuperGLUE which replaces an older platform called GLUE with a “much harder benchmark with comprehensive human baselines,” according to Facebook AI. 

SuperGLUE helps to put NLP abilities to the test where previous benchmarks were beginning to pose too simple for the latest systems.

“Within one year of release, several NLP models have already surpassed human baseline performance on the GLUE benchmark. Current models have advanced a surprisingly effective recipe that combines language model pretraining on huge text data sets with simple multitask and transfer learning techniques,” Facebook said.

In 2018, Google released BERT (Bidirectional Encoder Representations from Transformers) which Facebook calls one of the biggest breakthroughs in NLP. Facebook took Google’s open-source work and identified changes to improve its effectiveness which led to RoBERTa (Robustly Optimized BERT Pretraining Approach).

RoBERTa basically “smashed it,” as the kids would say, in commonly-used benchmarks:

“Within one year of release, several NLP models (including RoBERTa) have already surpassed human baseline performance on the GLUE benchmark. Current models have advanced a surprisingly effective recipe that combines language model pretraining on huge text data sets with simple multitask and transfer learning techniques,” Facebook explains.

For the SuperGLUE benchmark, the consortium decided on tasks which meet four criteria:

1. Have varied formats.
2. Use more nuanced questions.
3. Are yet-to-be-solved using state-of-the-art methods.
4. Can be easily solved by people.

The new benchmark includes eight diverse and challenging tasks, including a Choice of Plausible Alternatives (COPA) causal reasoning task. The aforementioned task provides the system with the premise of a sentence and it must determine either the cause or effect of the premise from two possible choices. Humans have managed to achieve 100 percent accuracy on COPA while BERT achieves just 74 percent.

Across SuperGLUE’s tasks, RoBERTa is currently the leading NLP system and isn’t far behind the human baseline:

You can find a full breakdown of SuperGLUE and its various benchmarking tasks in a Facebook AI blog post here.

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