Editor’s note: Meet Gareth Walkom, an entrepreneur dedicated to helping others with speech disorders.

Turning life experience into innovation

Did you know that 3% of Americans have a speech disorder, while 1% of the world’s population have a stutter? Just getting what they need in everyday interactions can be stressful, which intensifies when the stakes are raised during job interviews, presentations, public speaking, and other activities. As a result, some people with speech disorders may avoid conversations and relationships, and risk being denied jobs because of a difference in how they speak.

As a person who stutters, I know firsthand the ableism that people with a speech disorder can encounter in wanting to use their voice in a judgemental world: the frustration of sometimes not being able to say exactly what you want to say and therefore speaking less in speaking situations. And the educational and career opportunities are lost when doors remain closed to us, especially when employers advertise their jobs as requiring someone who speaks the language ‘fluently’.

While researchers still don’t definitively know what causes stuttering, emerging technologies are giving us new and promising pathways for improving the quality of life of people with speech disorders. 

That’s why after years of researching and testing potential therapeutic uses of virtual reality, and with the support of the Google for Startups Cloud Program, I founded withVR on International Stuttering Awareness Day (October 22) in 2020. The mission of withVR is to prepare people with speech disorders for real-life speaking situations by utilizing the power of virtual reality. 

Working through it

One of the difficulties in adapting to any disability is the opportunity to work through it in a safe and nonjudgmental environment. withVR provides a virtual space for individuals, in collaboration with their speech therapists, to practice real-world speaking scenarios in safe, controlled environments. 

Imagine being able to raise your hand in class and give your opinion without hesitation, ordering the meal you want rather than something that’s easier to say, or sit across the table from an avatar of an employer and explain why you are the right person for your dream job. Then further customize the speaking situation and its surroundings to challenge yourself and be ready for anything. That’s what withVR offers individuals and their speech therapists.

Making VR come to life

To bring the withVR vision to life, we are developing applications using the Unity game engine on Google Cloud with integrated Firebase services including authentication, web hosting, storage, and database. It’s a powerful combination that’s enabled us to build industrial-strength applications that we’ve rapidly deployed on a global basis. Today we are already collaborating with 80+ labs, clinics, and hospitals in more than 20 different countries worldwide.

These organizations help us to test and refine a virtual reality application to support people in achieving their speech goals and build comfort through immersive VR experiences using easily available viewers like Google Cardboard. 

The application works in conjunction with a web app through which speech therapists configure customized VR scenarios for their patients to use. As no real-life speaking situation is ever exactly the same, customization of VR scenarios is vital. They can construct different scenes, create and script avatars, and through the Google Text-to-Speech API can even choose from hundreds of different voices in a variety of languages. This gives them the flexibility to create many unique speaking situations for their clients no matter where they are in the world.

Progress from the practice sessions is presented through a dashboard that provides therapists with a tool to monitor their clients’ progress and provide feedback and encouragement.

No shortage of support

My founder’s journey has been supported by many passionate people. The Google for Startups Cloud Program has been instrumental in helping us come so far in the first year, and we’ve only scratched the surface of what’s possible. There are many capabilities in Firebase and Google Cloud that we have yet to explore, and through the startup program I now have a Google Mentor who can help guide that exploration. 

We also joined the 2Gether-International (2GI) Tech Cohort, which is supported by Google for Startups and is built for and run by entrepreneurs with disabilities. At the end of the 10-week cohort, we finished with a pitch competition, where I was one of six selected founders to pitch in just three minutes. I was very fortunate to win the Best Overall Pitch Award, gaining 10,000 USD in seed funding. This award not only highlights the potential of withVR, but also showcases that anyone can pitch their idea in a short amount of time no matter their difference. 

Working with 2GI also gave me the opportunity to collaborate and learn from other founders who have disabilities. It’s a safe space where I don’t have to explain my everyday challenges and can focus on the all-important task of advancing the vision of withVR, while seeing how others use technology in their domain. 

Building on a strong foundation

I’m amazed to look back and see what we’ve accomplished in just one year and humbled by the thousands of lives we’ve touched. Every day we receive valuable real-life feedback from people in the field—both clinicians and those with speech differences who benefit from VR therapy. That knowledge tells us that we are heading in the right direction and opening our eyes to new possibilities for where to take withVR. And inspiring us to keep moving ahead.

If you’d like to participate in testing or if you are speech therapist or researcher, please feel free to reach out to us. We’d love to show you how you can contribute to a world where anyone with a speech disorder can truly use their voice in any situation. If you’d like to take part, contact us at hello@withvr.app.

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

According to a National Academy of Medicine discussion paper, social determinants of health (SDoH) account for upwards of 80% of a population’s health outcomes. Breaking this down further, 50% come just from socioeconomic and physical environment factors such as education, employment, income, family and social support, community safety, air and water quality, and access to housing and transit. SDoH determine access to and quality of healthcare, and are contributors to a system of disparate access to care.

We believe that to more efficiently provide comprehensive healthcare access to more people, providers will leverage technology to blend in-person and virtual modes of care delivery.

In this article, Amwell and Google Cloud examine five ways telehealth – as part of a provider’s overall care model – can help democratize access to healthcare. (graphic url) 

Remove distance as a barrier to care

8.6 million Americans live more than 30 minutes from their nearest hospital. Long drives can deter patients from seeking care or maintaining routine visits. On the flip side, 92% of Americans nationwide have access to wired broadband in the home or through mobile broadband. Therefore, having a virtual visit just a click away can help remove barriers to care, like distance.

Eliminate the risk of unnecessary exposure

Virtual care means that patients don’t have to worry about potential exposure in transit, while sitting in waiting rooms, or from direct interactions during in-person health visits. This is particularly relevant when it comes to those with chronic diseases or underlying conditions. Telehealth provides patients who may be more susceptible to diseases with access to continuous healthcare without putting them at higher risk for developing more severe symptoms. Virtual visits can occur in the comfort –and safety– of patients’ homes.

Extend access to specialized care

55% of preventable hospitalization or mortality in rural settings is due to lack of access to specialty care. With telehealth, physical proximity to specialized services–typically in urban areas–can be reduced as a limiting factor. Virtual solutions grant everyone access to top specialists, regardless of location.

Save time and money

By augmenting in-person visits with telehealth applications, providers can benefit from greater efficiencies in scheduling, helping to improve their bottom line, and add more flexibility to their workday. Meanwhile, patients can spend less on travel and childcare, limit time taken off work, and save on other costs associated with in-person visits — for a savings of $35 to $690 per visit. In a survey by the COVID-19 Healthcare Coalition, 76% of the 2,000+ patients surveyed across the US responded that transportation was removed as a barrier, 65% reported they no longer had to take time off from work for an appointment, and 67 percent reporting lower costs than an in-person visit.

Combat physician shortage and fatigue

Research shows there will be a shortage of more than 100,000 doctors by 2030. In the midst of a physician shortage, telehealth can help improve care delivery and make it more efficient, ensuring more people can still have their healthcare needs addressed. Additionally, by integrating intelligence such as case triaging along with telehealth into a virtual care model, providers can help reduce clinician burnout.

Amwell and Google Cloud are partnering to deliver transformative telehealth solutions that will make it easier for more patients to receive care and improve patient and clinician experiences across the continuum of care. One example includes embedding real-time captioning and translation services powered by Google Cloud’s AI and NLP technologies within the Amwell platform to increase health access and understanding for more people.

As physicians, we are excited that the future of healthcare will continue to blend cloud technologies like EHR-integrated telehealth platforms, AI, healthcare-trained virtual agents along with in-person care to create an integrated hybrid care model that will improve patient outcomes and unburden providers, all while expanding access to broader patient populations.

To learn more, download the whitepaper “Healthcare’s Virtual Transformation,” written in conjunction with Becker’s Hospital Review.

^{1: “Social Determinants of Health 101 for Health Care: Five Plus Five,” National Academy of Medicine, October 2017}

Google Cloud’s AI-optimized infrastructure makes it possible for businesses to train, fine-tune, and run inference on state-of-the-art AI models faster, at greater scale, and at lower cost. We are excited to announce the preview of inference on Cloud TPUs. The new Cloud TPU v5e enables high-performance and cost-effective inference for a broad range AI workloads, including the latest state-of-the-art large language models (LLMs) and generative AI models.

As new models are released and AI becomes more sophisticated, businesses require more powerful and cost efficient compute options. Google is an AI-first company, so our AI-optimized infrastructure is built to deliver the global scale and performance demanded by Google products like YouTube, Gmail, Google Maps, Google Play, and Android that serve billions of users — as well as our cloud customers. 

LLM and generative AI breakthroughs require vast amounts of computation to train and serve AI models. We’ve custom-designed, built, and deployed Cloud TPU v5e to cost-efficiently meet this growing computational demand.

Cloud TPU v5e is a great choice for accelerating your AI inference workloads: 

• Cost Efficient: Up to 2.5x more performance per dollar and up to 1.7x lower latency for inference compared to TPU v4.
• Scalable: Eight TPU shapes support the full range of LLM and generative AI model sizes, up to 2 trillion parameters. 
• Versatile: Robust AI framework and orchestration support. 

In this blog, we’ll dive deeper into how you can leverage TPU v5e effectively for AI inference.

Up to 2.5x more performance per dollar and up to 1.7x lower latency for inference

Each TPU v5e chip provides up to 393 trillion int8 operations per second (TOPS), allowing complex models to make fast predictions. A TPU v5e pod consists of 256 chips networked over ultra-fast links. Each TPU v5e pod delivers up to 100 quadrillion int8 operations per second, or 100 PetaOps, of compute power.

We optimized the Cloud TPU inference software stack to take full advantage of this powerful hardware. The inference stack leverages XLA, Google’s AI compiler, which generates highly-efficient code for TPUs to maximize performance and efficiency.

The combined hardware and software optimizations, including int8 quantization, enable Cloud TPU v5e to achieve up to 2.5x greater inference performance per dollar than Cloud TPU v4 on state-of-the-art LLM and generative AI models, including Llama 2, GPT-3, and Stable Diffusion 2.1:

Google Internal Data. August 2023. Normalized to single-chip throughput. Precision: Llama 2 7B, 13B, 70B, GPT-J 6B: int8; GPT-J 175B, Stable Diffusion 2.1: bf16.

On latency, Cloud TPU v5e achieves up to 1.7x speedup compared to TPU v4:

Google Internal Data. August 2023. Precision: Llama 2 7B, 13B and 70B: int8; GPT-3 175B: bf16.

Google Cloud customers have been running inference on Cloud TPU v5e, and some have seen even greater speedups on their particular workloads.

AssemblyAI offers dozens of AI models to their customers for speech recognition and understanding with over 25 million inference calls on a daily basis. 

“Cloud TPU v5e consistently delivered up to 4X greater performance per dollar than comparable solutions in the market for running inference on our production model. The Google Cloud software stack is optimized for peak performance and efficiency, taking full advantage of the TPU v5e hardware that was purpose-built for accelerating the most advanced AI and ML models. This powerful and versatile combination of hardware and software dramatically accelerated our time to solution: instead of spending weeks hand-tuning custom kernels, within hours we optimized our model to meet and exceed our inference performance targets.” – Domenic Donato, VP of Technology, AssemblyAI

Scale to the full range of LLM and Generative AI model sizes 

LLMs and generative AI models continue to grow in size and computational cost. The largest models require the combined compute and memory of hundreds of hardware accelerators. Cloud TPU v5e enables inference for a wide range of model sizes. A single v5e chip can run models with up to 13B parameters. From there, you can scale up to hundreds of chips and run models with up to 2 trillion parameters.

Google Internal Data. August 2023. Batch size = 1. Multi-head attention based decoder only language models: prefix length = 2048, decode steps = 256, beam size = 32 for sampling.

Gridspace leverages Google Cloud TPU infrastructure to power its full-stack conversational AI platform – building and integrating real-time conversational ASR, LLMs, semantic search, and neural TTS.

“We’re a huge fan of Google Cloud TPUs. Our benchmarks are demonstrating a 5X increase in the speed of AI models when training and running on Google Cloud TPU v5e. We are also seeing a 6x improvement in the scale of our inference metrics. We’ve scaled our AI models to billions of conversations per year across financial services, capital markets, and healthcare with Google Cloud’s AI infrastructure. Our Grace bots are powered by models trained using Cloud TPUs and served at scale on GKE with support for PCI, HITRUST, and SOC 2 compliance.” – Wonkyum Lee, Head of Machine Learning, Gridspace 

Robust AI framework and orchestration support

Leading AI frameworks, including PyTorch, JAX, and TensorFlow, provide robust support for inference on Cloud TPU v5e. This means you can now train and serve models end-to-end on Cloud TPUs: what you train is what you serve.

Google Cloud offers you many choices to run inference on Cloud TPUs easily and reliably. From GKE and Vertex AI, to popular open-source frameworks such as Ray and Slurm, you can leverage Google Cloud TPUs in your preferred way to fit your development process.

Try Cloud TPU v5e for inference today

Cloud TPU v5e provides a high-performance, cost-efficient, scalable, and reliable inference platform for LLMs and generative AI models. Leading AI companies are leveraging the power of Cloud TPU v5e to serve AI models at scale:

To get started with inference on Cloud TPU, reach out to your Google Cloud account manager or contact Google Cloud sales.