Monthly Archives: June 2021

Dr. Zsolt Garami, medical director of the vascular ultrasound lab at Houston Methodist Hospital, puts it very straightforward: Transcranial Doppler (TCD) is one of the least understood, rarely utilizedand potentially most valuable tools available for monitoring brain circulation.

THE PROBLEM

TCD was introduced by Aaslid in 1982. Thanks to the addition of power M-mode Doppler (PMD) in 2000, TCD can detect not only the presence of blood flow, but also its depth, direction and resistance (DDR), he explained.

"TCD provides great sensitivity in detecting foreign particles, known as emboli, as small as 40 microns in diameter present in the blood cell stream," he said. "As a noninvasive, safe and cost-effective method for evaluating cerebrovascular circulation, TCD is the 'stethoscope for the brain.'"

Emboli detected on TCD are referred to as HITS (high-intensity transient signals) and the TCD machine provides both a visual and auditory signal of their presence. Emboli traveling up the carotid system pass from deep in the brain, generating unique sound and images.

"Even with all its benefits, TCD is underutilized as it requires a trained sonographer to perform an exam," Garami noted. "In addition, interpretation of the captured signal is not taught in school, leaving only experienced physicians able to understand the value of the data provided by the detailed waveform images."

PROPOSAL

NovaSignal is a medical technology and data company that offers NovaGuide, a cerebrovascular monitoring system.

The company worked to attack TCD's primary shortcomings. The fully automated, robotic NovaGuide minimizes the need for a trained sonographer, and its AI algorithms assist with the reading of the captured waveforms.

Dr. Zsolt Garami, Houston Methodist Hospital

"The robotic probe pods automatically identify the acoustic window in the temple that allows for the pulsed Doppler ultrasound to view blood flow in the brain," Garami explained. "This acoustic window varies from individual to individual, leading to variability in manual exams, even when performed by well-trained sonographers.

"NovaGuide eases that burden by automatically identifying the signal," he continued. "Furthermore, once the signal is acquired, NovaSignal has introduced novel AI algorithms to further aid in the interpretation of the cerebral blood flow velocity waveforms."

MEETING THE CHALLENGE

NovaGuide opens the opportunity for "green" medical staff, nurses without any TCD training or experience, to learn and use the robotic TCD system in just a few hours, Garami reported.

"With four billable clinical codes assigned to TCD, NovaGuide is economically suitable for big academic hospitals as well as small practices," he noted. "Specifically, for those centers with TCD experience, NovaGuide provides an automated solution to ease the clinical burden of longer exams. Additionally, if the site does not have the expertise required, NovaGuide provides access with just a few hours of training.

"TCD's sensitivity in detecting emboli presents an advantage for PFO tests where agitated air is deliberately injected into a systemic vein and shown passing into the cerebral circulation via the hole in the heart," he added.

"Without the hole, the air would be filtered out by the lungs. We are currently conducting a research trial with NovaGuide to prove that this indirect diagnostic mode is the most sensitive test for PFO and not as uncomfortable as swallowing a tube in sedation for the cardiac ultrasound."

At Houston Methodist Hospital, NovaGuide exports clinical reports to the PACS system for easy viewing and interpretation of the final reports.

RESULTS

There have been several clinical scenarios at the hospital where NovaGuide has provided concrete clinical evidence to help support the management of patients. A few specific examples revolve around the use within the operating theater for cardiac procedures.

"It has been well established that embolization occurs during a variety of cardiac procedures and the use of TCD can inform on how to change clinical practice to reduce these perioperative emboli and reduce stroke risk," Garami explained.

"Multiple protection filters were developed to clean the blood flow from these materials. TCD helps to test these and, even early in development, to decide which could be more effective to use.

"I believe this technology has the ability to improve outcomes of those procedures, as it is the only tool able to provide real-time information about embolization during manipulation of the procedure," he continued.

"In addition to emboli monitoring, we are currently using the system to assess and compare pre- and post-procedure cerebral hemodynamics to ensure the operation has accomplished the necessary clinical impact by restoring improved cerebral blood flow."

This can be done in real time at the bedside, before the patient is removed from the operating room.

"In addition to the operating room, the use of the NovaGuide has applications in the recovery room, intensive care unit and on the floor, as it provides bedside hemodynamic monitoring, a distinct advantage when compared to 'static' radiological images like CT, MRI, DSA, etc.," Garami said.

"Within these environments, TCD has many well-accepted clinical uses: vasospasm detection after intracranial bleeding, detecting large vessel occlusion in stroke/TIAs, detection of intracranial stenoses, PFO bubble test ... The list can be endless to utilize this technology."

ADVICE FOR OTHERS

TCD provides unique access to monitoring of cerebral hemodynamics in the large arteries of the brain and the ability to monitor emboli events. The technology is a noninvasive, safe and cost-effective method for evaluating cerebrovascular circulation, and complements existing "static" imaging, Garami advised.

"Unfortunately, the technology has been limited due to the difficulty in signal acquisition leading to some negative opinions by nonusers," he noted:"'I do not want to know about this emboli;it has no clinical manifestations,' or, 'The results are user-dependent and cannot be trusted.'

"The obvious retort is, 'Explain to me what kind of emboli do good when going up into the brain? Do you know what is going on in your brain?'

"We have long waited for changes to come to TCD, and we are excited about the opportunity to see the technology continue to expand," he concluded.

Twitter:@SiwickiHealthITEmail the writer:bsiwicki@himss.orgHealthcare IT News is a HIMSS Media publication.

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Houston Methodist uses AI brain ultrasound to reduce open heart surgery complications - Healthcare IT News

The startup investing market is crowded, expensive and rapid-fire today as venture capitalists work to preempt one another, hoping to deploy funds into hot companies before their competitors. The AI startup market may be even hotter than the average technology niche.

This should not surprise.

In the wake of the Microsoft-Nuance deal, The Exchange reported that it would be reasonable to anticipate an even more active and competitive market for AI-powered startups. Our thesis was that after Redmond dropped nearly $20 billion for the AI company, investors would have a fresh incentive to invest in upstarts with an AI focus or strong AI component; exits, especially large transactions, have a way of spurring investor interest in related companies.

That expectation is coming true. Investors The Exchange reached out to in recent days reported a fierce market for AI startups.

The Exchange explores startups, markets and money.

Read it every morning on Extra Crunch or get The Exchange newsletter every Saturday.

But dont presume that investors are simply falling over one another to fund companies betting on a future that may or may not arrive. Per a Signal AI survey of 1,000 C-level executives, nearly 92% thought that companies should lean on AI to improve their decision-making processes. And 79% of respondents said that companies are already doing so.

The gap between the two numbers implies that there is space in the market for more corporations to learn to lean on AI-powered software solutions, while the first metric belies a huge total addressable market for startups constructing software built on a foundation of artificial intelligence.

Now deep in the second quarter, were diving back into the AI startup market this morning, leaning on notes from Blumberg Capitals David Blumberg, Glasswing Ventures Rudina Seseri, Atomicos Ben Blumeand Jocelyn Goldfein of Zetta Venture Partners. Well start by looking at recent venture capital data regarding AI startups and dig into what VCs are seeing in both the U.S. and European markets before chatting about applied AI versus core AI and in which context VCs might still care about the latter.

The exit market for AI startups is more than just the big Microsoft-Nuance deal. CB Insights reports that four of the largest five American tech companies have bought a dozen or more AI-focused startups to date, with Apple leading the pack with 29 such transactions.

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AI startup investment is on pace for a record year - TechCrunch

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--The AI Hardware Summit, September 13-16, 2021 returns to the Computer History Museum, Mountain View, for its fourth iteration, having sold out the venue each previous year. As the first hybrid event in its industry, attendees can benefit from tickets to attend in-person; or virtual tickets to tune in from across the globe.

The 2021 AI Hardware Summit has evolved. As machine learning models continue to grow in size and complexity and enter production in enterprises and institutions worldwide, the approach to accelerating these workloads is shifting. With support from Headline Partner, Synopsys, and Platinum Partners; Cadence, Graphcore, Habana, Intel and SambaNova Systems, this years summit has shifted from focusing solely on hardware to taking a holistic view on AI acceleration at the systems level.

Presentations feature multidisciplinary perspectives on building and deploying fast, efficient, and affordable AI systems, from 50+ speakers drawn from the AI hardware user and technology vendor ecosystems. Topics include:

The AI Hardware Summit hosts more than 600 C-suite and engineering specialists across the machine learning technology stack.

Previous event highlights include AI hardware start up, Habana Labs, (acq. by Intel, 2019) emerging from stealth at the event in 2018, and Chairman of Alphabet Inc. & former President of Stanford University, John Hennessy, giving a luminary keynote in 2019.

This year keynote speakers include Aart de Geus, Chairman & Co-CEO, Synopsys and Lip-Bu Tan, CEO, Cadence.

The AI Hardware Summit is a great place where lots of people interested in AI Hardware come together and exchange ideas, and together we make the technology better. Theres a synergistic effect at these summits which is really amazing and powers the entire industry. John Hennessy, Chairman, Alphabet Inc.

Expect limitations on the availability of live tickets, dependent on Covid-19 US government guidance and regulations. Registration to attend AI Hardware Summit starts from only $999 for an in-person ticket, and $499 for virtual tickets.

To find out more, visit http://www.aihardwaresummit.com

Excerpt from:

AI Hardware Summit: Must-Attend AI Event Releases Agenda Ahead of its Return to Face-to-Face in Silicon Valley - Business Wire

The innovation is a collaboration between AP-HP Greater Paris University Hospitals and Owkin, a start-up pioneering federated learning and Artificial Intelligence (AI) technologies for medical research and clinical development. The tool, which is a trained and validated AI model, can be used in clinical practice worldwide and opens the possibility of patient molecular stratification in routine care and for clinical trials.

The results of the companies ongoing strategic collaboration was presented at ASCO 2021. The abstract and poster, entitled Identification of pancreatic adenocarcinoma molecular subtypes on histology slides using deep learning models, demonstrates the first AI-based tool for predicting genomic subtypes of pancreatic cancer (PDAC) developed from machine learning applied to histology slides.

Gilles Wainrib, Chief Scientific Officer and Co-Founder of Owkin, said: Our research shows AI can help connect information at the genomic, cellular and tissue levels, and how doing so can bring immediate value to make precision medicine a reality for patients. This study further underscores the value of using machine learning for identifying histo-genomic signals for cancer research and clinical development.

Pancreatic adenocarcinoma is a complex and heterogeneous disease. Heterogeneity and tumour plasticity are likely major factors in the failure of many clinical trials. Multiomics studies have revealed two main tumour transcriptomic subtypes, Basal-like and Classical, that have been proposed to be predictive of patient response to first-line chemotherapy. The determination of these subtypes has been possible so far by RNA sequencing, a costly and complex technique that is not yet feasible in a clinical routine setting. Taken together, these factors make it compelling to use advanced AI methods with common histological slides, trained alongside crucial context from expert researchers, to address the unmet needs of patients.

Professor Jrme Cros, Pathologist at Beaujon Hospital, Universit de Paris, said: This tool was developed using the unique histological and molecular resources from four APHP hospitals through a unique collaboration between pathologists from APHP, bioinformaticians from the group Carte dIdentit des Tumeurs de la Ligue Contre le Cancer, and data scientists from Owkin. It can remotely subtype tumour in minutes, paving the way for many applications from basic science to clinical practice.

This research is part of a successful and ongoing collaboration between Owkins multidisciplinary teams and those of the AP-HP Greater Paris University Hospitals. Since 2019, the two have collaborated in the service of shared objectives: to improve patient care and facilitate the development of new drugs in three main areas (oncology, immunology, cardiology), and to democratise access to AI for researchers to promote innovation and medical advances.

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AI-based tool could improve pancreatic cancer research and treatment - Health Europa

If there are ways AI can expedite diagnoses while protecting sensitive data, would medical networks use it? The short answer is yes, but there are still challenges facing the healthcare industry when it comes to encrypting data and sharing it. While the benefits are apparent, medical networks cant shake the burden of protecting their patientsnor do they want to.

There are various use cases in which implementing AI in medical imaging would benefit patient care and assist clinicians in diagnosing:

AI-assisted imaging can decrease time to diagnose patients with chronic diseases by flagging areas of concern and even clarifying images, making it a little easier for clinicians to examine.

During A3s Vision Week, Stacey Shulman, VP of the Internet of Things group and general manager of Health, Life Sciences and Emerging Technologies at Intel, discussed the potential of AI-powered medical imaging, as well as the challenges the industry faces.

We, as consumers, have digital access to nearly every part of our life, she began. I can get my DNA information digitally, but I still cant get a copy of my X-rays.

With the exception of entities like the Mayo Clinic and the VA Health Care System, who are already using some pretty advanced technologies, many healthcare systems are behind the transformation curve.

Shulman explained results from an Intel and Concentrix survey on how the medical industry is viewing AI. Before the pandemic (in 2018), 54% of respondents expected widespread AI adoption. During the pandemic (2020), that percentage jumped to 84%.

This means the medical community is starting to have the digital transformation conversation. Thats not the medical industrys fault, though. Its limited by the data it can share and the needs of the developer community. To train AI models, data is a requirement.

Shulman pointed out that an obvious solution would be to decrease data protections, but also noted that likelihood was not high.

Data isolation would be another solution. Keeping data secure and close to the point of origination would enable organizations to leverage its insights. Another issue is the size of the data. The amount of data generated is enormous and transmission issues would occur.

This is where federated learning can lend a hand. The idea is to train models on distributed and private datasets without moving them and then create a network of models based on region.

The concept of dont move the data, move the algorithm to the data, Shulman explained. That area of disaggregation is something were seeing quite a bit.

Most hospital networks dont have in-house AI capabilities, so getting the developer community involved is another issue at hand. Developers need data to train models, which hospitals cant give up easily.

The way I like to look at artificial intelligence in the medical industry is it really needs to become the new operating system, she said. We need to take artificial intelligence and move it into the device itselfand then we need to take that patient information and that connected information, build robust models so that we understand regional healthso we can detect faster.

She explained that the robust regional models should be combined in national and even global models so we can understand disease spread and trends.

I feel pretty hopeful about where the industry is going, Shulman said. For the healthcare industry, we have to start making baby steps in the industry to get artificial intelligence providing real results.

Excerpt from:

How to Get Past the Stalemate Between AI and the Medical Industry - Machine Design

Artificial intelligence (AI) is one of the fastest-growing technological industries today, but what effects will it have on legal practices? In addition to the growing number of legal questions that arise as the explosive growth of AI creeps into our everyday lives, artificial intelligence is already enabling some software to carry out legal functions. Lets discuss the future of AI in law.

Artificial intelligence, simply put, is teaching computers to think the way humans would, using the given data and desired output requested. There are many different types of systems that utilize AI, from advertising and marketing to shopping, to scheduling. These AI systems, also referred to as narrow AI, are not what many people think of when they imagine artificial intelligence. Typically, what may come to mind are human-like computers, such as those featured in movies and television, capable of complex thought and emotion.

In reality, AI is most often used to carry out specific tasks that require a very concentrated skillset, and AI allows a programmer to teach a computer to perform these specialized tasks extremely proficiently.

AI is often used for things such as navigation, analyzing large datasets, organizing and ordering inventory, and other tasks that are time-consuming and tedious. AI can also be used to translate spoken or written language, and help make decisions by determining likely outcomes. AI is used by a huge variety of industries, as well as by individuals.

AI shines when it comes to increasing efficiency. This can be seen in scheduling, planning, data management, and other tasks that typically require the dedication of large amounts of time. Within the legal industry, huge amounts of data often need to be analyzed or searched for keywords, making AI a powerful tool.

Artificial intelligence is great at recognizing patterns, which is the primary way computers are able to learn. This means that AI is perfect for analyzing large amounts of documents and materials, which can help with a huge number of tasks relevant to legal professions.

AI is not yet able to compose legal documents, advise clients, or replicate the services of a lawyer inside of a courtroom. Since AI is dependent on human directives, inputted data, and incapable of certain types of critical thinking, AI is limited by the way in which it is built. As AI becomes more capable of independent decision making, new challenges continue to pop up, as well as legal, moral and ethical dilemmas.

AI is already being used to review legal documents, as well as assist in research prior to or during a case. Particularly when cases have large amounts of paperwork that would take a significant amount of time to sift through, AI is helpful in making sure documents with certain keywords get pushed to the top of the stack.

Another way AI is being used by legal professionals is to understand risk and understand the best way to advise their clients. AI can analyze contracts both in bulk and individually much more efficiently than a human could.This makes it much easier to make comments, allows firms to quickly move through contracts, and reduces the number of mistakes and overlooked details. AI is incredibly efficient, which means it can perform legal research much faster, so lawyers are able to build better cases.

AI is even being used to predict how likely it is that a legal team will win a case, based on all of the relevant data available from similar cases and proceedings. This lets lawyers know the probability of profit and loss when taking on a new case, as well as the best way to proceed, so they have the highest chance of success.

Lawyers are not only reluctant to incorporate any type of technology to their business that may compromise the privacy of their clients, they also dont want to minimize their billable hours. Not only that, but the learning curve that AI requires to integrate it successfully into a practice can be steep. This makes legal professionals even less likely to consider using AI as a tool to improve their business, since they typically do not have time to learn a new type of technology.

There are also laws being passed regarding AI and other new technologies that can be used by legal professionals, and they vary state to state. This makes it difficult to know whether new practices put in place may leave a practice vulnerable to legal action against them.

Artificial intelligence is already changing the legal landscape, and many legal professionals have expressed concern over how AI will directly impact their jobs. Although the legal industry is notoriously slow when it comes to adapting to new technologies and practices, the incorporation of artificial intelligence is inevitable. It is better to be on the forefront of this new frontier, than trying to keep up once AI has increased the speed and efficiency of competing law firms.

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Changing the Legal Landscape Through AI - The National Law Review

The report looks at how technological advances in areas like facial recognition and AI can be balanced with protecting human rights. Credit: PhotoMIX Company/Pexels

The conundrum is one that many governments face: how do you make the most of technological advances in areas such as artificial intelligence (AI) while protecting peoples rights? This applies to government as both a user of the tech and a regulator with a mandate to protect the public.

Australias Human Rights Commission recently undertook an exercise to consider this very question. Its final report, Human Rights and Technology, was published recently and includes some 38 recommendations from establishing an AI Safety Commissioner to introducing legislation so that a person is notified when a company uses AI in a decision that affects them.

We have rounded up some of the reports recommendations for governments about how to ensure greater use of AI-informed decision-making does not result in human rights disaster.

A range of recommendations in the report relate to improving the regulatory landscape around AI technology.

The report particularly singles out facial recognition and other biometric technology. It recommends legislation, developed in consultation with experts, to explicitly regulate the use of such technology in contexts like policing and law enforcement where there is a high risk to human rights.

More generally, the report calls for the establishment of an independent, statutory office of an AI Safety Commissioner. This body would work with regulators to build their technical capacity regarding the development and use of AI.

The AI Safety Commissioner would also monitor and investigate developments and trends in the use of AI, especially in areas of particular human rights risk, give independent advice to policy-makers and issue guidance on compliance.

Alongside this, the report notes that AI Safety Commissioner should advise government on ways to incentivise good practice [in the private sector] through the use of voluntary standards, certification schemes and government procurement rules.

Several of the reports recommendations focus on people who might be affected by AI. It calls for more public involvement in decisions about how AI should be used, and more transparency in indicating when a member of the public is affected by an AI-assisted decision.

For example, the report suggests legislation be introduced that would require any department or agency to complete a human rights impact assessment (HRIA) before an AI-informed decision-making system is used to make any administrative decision. Part of this HRIA should be a public consultation focusing on those most likely to be affected, the report says.

The report also notes that governments should encourage companies and other organisations to complete a HRIA before developing any AI-informed decision-making tools. As part of the recommendations, the authors suggest that the government appoints a body, such as the AI Safety Commissioner, to build a tool that helps those in the private sector complete the assessments.

In addition, the report recommends legislation to require that any affected individual is notified where artificial intelligence is materially used in making an administrative decision in government. There should also be equivalent laws binding private sector users of AI to do the same.

The report also says: The Australian Government should not make administrative decisions, including through the use of automation or artificial intelligence, if the decision maker cannot generate reasons or a technical explanation for an affected person.

Other recommendations also suggest that the Australian government improve its capacity for working ethically with AI-informed decision-making tools.

The government should convene a multi-disciplinary taskforce on AI-informed decision making, led by an independent body, such as the AI Safety Commissioner, the report says. Responsibilities should include promoting the use of human rights by design in AI.

In keeping with the theme of transparency, the report also recommends that centres of expertise, such as the Australian Research Council Centre of Excellence for Automated Decision-Making and Society, should prioritise research on the explainability of AI-informed decision making.

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Human rights and AI: interesting insights from Australia's commission - Global Government Forum

The University of Illinois Urbana-Champaign Grainger College of Engineering is partnering with tech giant IBM to bolster the colleges research and workforce development efforts in quantum information technology, artificial intelligence and environmental sustainability.

According to a news release from the university, the 10-year $200 million partnership will fund the future construction of a new Discovery Accelerator Institute, where university and IBM researchers will collaborate on solving global challenges with emerging technologies such as AI.

Areas of study will include AI's potential to solve sustainable energy, new materials for CO2 capture and conversion, and cloud computing and security. Researchers will also explore ways to improve quantum information systems and quantum computing, which applies the rules of quantum mechanics to make computations much faster than most computers in use today.

Bashir said the partnership will allow IBM and university researchers to work toward developing the technology of tomorrow, with sustainability in mind.

Were looking for a new way to really bridge that gap [between academia and the tech industry] in a much more intimate way and expand our collective research and educational impact, he said. In higher ed and industry, we need to come together to solve grand challenges to keep a sustainable planet, to provide high-quality jobs and develop a new economy.

We had already been working with them in the AI space, Welser said. We realized we could take what were doing here with AI, expand it to do some of the work in the hybrid cloud space, and think about what we do with that by advancing these base technologies.

Its also using this as a test bed for what we call discovery acceleration, which is using technologies to discover new materials and new science that can help with societal problems, he continued. In the case of this, were focusing on carbon capture, carbon accounting and climate change.

As part of the initiative, Bashir said the company and faculty will team up to develop nondegree tech certification programs and professional development courses in IT-related fields. He said the goal will be to feed IT talent into the workforce, given the national shortage of tech professionals in artificial intelligence, data science and quantum computing.

Working with IBM, theyre interested in hiring the workforce of tomorrow. Building that talent from early in the pipeline and diversifying the STEM talent pipeline is something we want to work on together, he said, adding that the partnership also aims to diversify the IT talent pool by bringing students of color and women into emerging fields like quantum computing.

Welser said the Discovery Accelerator Institute will complement a related company initiative: the IBM Skills Academy, a training certification program that provides over 330 courses relating to artificial intelligence, cloud computing, blockchain, data science and quantum computing.

We have courses that help train professors in specific areas of these skills, and they can use those materials in their coursework and create their own accredited courses, he said. Weve realized there really is a need for having these kinds of courses that dont necessarily go into a full university [degree] but could be more certifications for students people who want to learn about an area and get a certain level of certification.

In addition to research and course development efforts, Bashir noted that the institute will give students close access to one of the worlds largest tech employers.

We believe we can work together to prepare more talent through our educational pipeline, which IBM can have firsthand access to, he said. If they are working together with us, then they get to know those students.

The Illinois initiative comes two months after the tech company announced a partnership with Cleveland Clinic to study hybrid cloud, AI and quantum computing technologies to accelerate advancements in health care and life sciences. As part of that partnership, IBM plans to install its first private-sector, on-premises quantum computing system in the U.S.

Continued here:

University of Illinois and IBM Researching AI, Quantum Tech - Government Technology

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Hello and welcome to Daily Crunch for June 9, 2021. Today was TC Sessions: Mobility, a rollicking good time and one that we hoped you enjoyed. Looking ahead, were starting to announce some speakers for Disrupt including Accels Arun Mathew. Mark your calendars, Disrupt is going to be epic this year. Alex

To round out our startup news today, two things: The first is that Superhuman CEO Rahul Vohra and his buddy Todd Goldberg, the founder of Eventjoy, have formalized their investing partnership in a new fund called Todd and Rahuls Angel Fund. That name has big Bill and Teds Excellent Adventure vibes, albeit with a larger, $24 million budget.

And fresh on the heels of the Equity Podcast diving into hormonal health and the huge startup opportunity that it presents, theres a new startup working on PCOS on the market. Check out our look at its early form.

SEO expert and consultant Eli Schwartz will join Managing Editor Danny Crichton tomorrow to share his advice for everyone who gets nervous each time Google updates its algorithm.

To set a foundation for tomorrows chat on Twitter Spaces, Eli shared a guest post that should deflate some myths. For starters: A drop in search traffic isnt necessarily hurting you.

Instead of chasing the algorithm, he advises companies that rely on organic search results to focus on the user experience instead: If you are helpful to the user, you have nothing to fear.

Just like you release product updates based on feedback and analytics, Googles improving its products to offer a better user experience.

If you see a drop, in many cases, your site might not have even lost real traffic, says Eli. Often, the losses represent only lost impressions already not converting into clicks.

Tomorrows discussion is the latest in a series of chats with top Extra Crunch guest contributors. If youve worked with a talented growth marketer, please share a brief recommendation.

(Extra Crunch is our membership program, which helps founders and startup teams get ahead. You can sign up here.)

TechCrunch is back with our next category for our Experts project: Were reaching out to startup founders to tell us who they turn to when they want the most up-to-date growth marketing practices.

Fill out the survey here.

Were excited to share the results we collect in the form of a database. The more responses we receive from our readers, the more robust our editorial coverage will be moving forward. To learn more, visit techcrunch.com/experts.

Join us for a conversation tomorrow at 12:30 p.m. PDT / 3:30 p.m. EDT on Twitter Spaces. Our own Danny Crichton will be discussing growth marketer Eli Schwartzs guest column Dont panic: Algorithm updates arent the end of the world for SEO managers. Bring your questions and comments!

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Daily Crunch: A crowded market for exits and acquisitions forecasts a hot AI summer - TechCrunch

How Alaska Airlines executed the perfect artificial intelligence use case. The company has saved 480,000 gallons of fuel in six months and reduced 4,600 tons of carbon emissions, all from using AI.

Image: Alaska Air

Given the near 85% fail rate in corporate artificial intelligence projects, it was a pleasure to visit with Alaska Airlines, which launched a highly successful AI system that is helping flight dispatchers. I visited with Alaska to see what the "secret sauce" was that made its AI project a success. Here are some tips to help your company execute AI as well as Alaska Airlines has.

SEE: Hiring Kit: Video Game Programmer (TechRepublic Premium)

Initially, the idea of overhauling flight operations control existed in concept only. "Since the idea was highly conceptual, we didn't want to oversell it to management," said Pasha Saleh, flight operations strategy and innovation director for Alaska Airlines. "Instead, we got Airspace Intelligence, our AI vendor, to visit our network centers so they could observe the problems and build that into their development process. This was well before the trial period, about 2.5 years ago."

Saleh said it was only after several trials of the AI system that his team felt ready to present a concrete business use case to management. "During that presentation, the opportunity immediately clicked," Saleh said. "They could tell this was an industry-changing platform."

Alaska cut its teeth on having to innovate flight plans and operations in harsh arctic conditions, so it was almost a natural step for Alaska to become an innovator in advancing flight operations with artificial intelligence.

SEE:Digital transformation: A CXO's guide (free PDF)(TechRepublic)

"I could see a host of opportunities to improve the legacy system across the airline industry that could propel the industry into the future," Saleh said. "The first is dynamic mapping. Our Flyways system was built to offer a fully dynamic, real-time '4D' map with relevant information in one, easy-to-understand screen. The information presented includes FAA data feeds, turbulence reports and weather reports, which are all visible on a single, highly detailed map. This allows decision-makers to quickly assess the airspace. The fourth dimension is time, with the novel ability to scroll forward eight-plus hours into the future, helping to identify potential issues with weather or congestion."

"We saved 480,000 gallons of fuel in six months and reduced 4,600 tons of carbon emissions." Pasha Saleh, flight operations strategy and innovation director for Alaska Airlines

The Alaska Flyways system also has built-in monitoring and predictive abilities. The system looks at all scheduled and active flights across the U.S., scanning air traffic systemically rather than focusing on a single flight. It continuously and autonomously evaluates the operational safety, air-traffic-control compliance and efficiency of an airline's planned and active flights. The predictive modeling is what allows Flyways to "look into the future," helping inform how the U.S. airspace will evolve in terms of weather, traffic constraints, airspace closures and more.

SEE:9 questions to ask when auditing your AI systems(TechRepublic)

"Finally the system presents recommendations," Saleh said. "When it finds a better route around an issue like weather or turbulence, or simply a more efficient route, Flyways provides actionable recommendations to flight dispatchers. These alerts pop up onto the computer screen, and the dispatcher decides whether to accept and implement the recommended solution. In sum: The operations personnel always make the final call. Flyways is constantly learning from this."

Saleh recalled the early days when autopilot was first introduced. "There was fear it would replace pilots," he said. "Obviously, that wasn't the case, and autopilot has allowed pilots to focus on more things of value. It was our hope that Flyways would likewise empower our dispatchers to do the same."

SEE:Graphs, quantum computing and their future roles in analytics(TechRepublic)

One step Alaska took was to immediately engage its dispatchers in the design and operation of the Flyways system. Dispatchers tested the platform for a six-month trial period and provided feedback for enhancing it. This was followed by on-site, one-on-one training and learning sessions with the Airspace Intelligence team. "The platform also has a chat feature, so our dispatchers could share their suggestions with the Airspace Intelligence team in real time," Saleh said. "Dispatchers could have an idea, and within days, the feature would be live. And because Flyways uses AI, it also learned from our dispatchers, and got better because of it."

While Flyways can speed times to decisions on route planning and other flight operations issues, humans will always have the role in route planning, and will always be the final decision-makers. "This is a tool that enhances, rather than replaces, our operations," Saleh said. Because flight dispatchers were so integrally involved with the project's development and testing, they understood its fit as a tool and how it could enhance their work.

"With the end result, I would say satisfaction is an understatement," Saleh said. "We're all blown away by the efficiency and predictability of the platform. But what's more, is that we're seeing an incredible look into the future of more sustainable air travel.

"One of the coolest features to us is that this tool embeds efficiency and sustainability into our operation, which will go a long way in helping us meet our goal of net zero carbon emissions by 2040. We saved 480,000 gallons of fuel in six months and reduced 4,600 tons of carbon emissions. This was at a time when travel was down because of the pandemic. We anticipate Flyways will soon become the de facto system for all airlines. But it sure has been cool being the first airline in the world to do this!"

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Flying high with AI: Alaska Airlines uses artificial intelligence to save time, fuel and money - TechRepublic