Categories
AI

Report: 13% fewer companies expect technology budgets to stay level or increase in 2023 vs. 2022

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.


Bain’s third annual global Technology Report, based on secondary market research, analysis of financial information and a range of interviews of industry participants, shows that although many companies are facing uncertainties due to current geopolitical and economic trends, these disruptions can often lead to advances.

According to Bain, 77% of companies are expected to either increase their technology budgets in 2023 or keep it the same; a dip from just last year when 90% of companies said they expected to either increase or keep their tech budgets the same come 2022.

And while tech companies are easily disrupted, Bain is reminding CIOs, CTOs and other technology executives that, despite rocky trends such as inflation and a looming recession, “technology will continue to play a central role in the global economy, helping to shape how companies in every sector create sustained value for customers and other stakeholders.”

Image source: Bain.

According to Bain, more than 75% of the largest venture capital investments in recent years went to IT infrastructure and industry-focused enterprise software companies, illustrating the potential for innovation.

Event

MetaBeat 2022

MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.

Register Here

AI investments growing as the tech increases market share

In addition to the findings above, Bain found that company investments in artificial intelligence (AI) are rapidly growing, and 86% of tech providers say AI is becoming critical for gaining market share and building customer loyalty.

Yet, according to Bain, only about 20% of companies have the technology infrastructure in place to make the most of AI’s potential. Today, AI is engaging customers, shaping product development and has the potential to transform industries alongside other Web3 technologies. Although these technologies can bring benefits, Bain also warns that they can bring implications for organizations who ignore Web3 capabilities.

Other technology trends covered by Bain

The comprehensive, almost 100-page report covered many other tech trends over the past year. Competing and winning in the multicloud world, scaling the industrial internet-of-things, increasing sales productivity in an economic downturn, consumption-based pricing, and the chip shortage are all covered. Some additional facts from the Bain report include:

  • In the race between cloud hyperscalers (e.g., AWS, Google Cloud) and multicloud infrastructure software vendors (e.g., Snowflake, Twilio), customers are already voting with their dollars, spending around 60% of their AI/ML budgets on hyperscalers’ tools, compared with 25% on multicloud ISV solutions.
  • For the industrial internet-of-things, the number of organizations implementing proofs of concept grew nearly 20% from 2018 to 2022 and is expected to grow another 20% by 2026.
  • The future is bright for software-as-a-service (SaaS) companies that employ consumption-based pricing: 80% of customers report better alignment with the value they receive from consumption pricing. And nearly half of software companies using it say it has helped them acquire more customers, while two-thirds say it’s helping them increase revenue with existing customers.

Methodology

Bain’s Technology Report 2022 is based on secondary market research, analysis of financial information available or provided to Bain and Company and a range of interviews with industry participants.

Read the full report from Bain.

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.

Repost: Original Source and Author Link

Categories
AI

6 AI companies disrupting healthcare in 2022

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.


Investments in AI-enabled healthcare have exploded over the past few years. But even with belt-tightening in 2022, digital health startups using artificial intelligence (AI) have received a whopping $3 billion in funding. That has left plenty of room for startup AI companies to make their mark in healthtech, biotech and medtech. 

It’s clear that even as health systems struggle to develop the right infrastructure to support AI’s need for vast data lakes, as well as to access quality or siloed data, the industry remains bullish on artificial intelligence. A December 2021 survey from health insurer Optum, for example, found that almost half of healthcare executives use AI, while around 85% say they have an AI strategy.

These are six startups that have had a banner year disrupting a variety of healthcare areas, from drug discovery and operational efficiency to disease detection and cell biology research.

Atomwise: AI for drug discovery

In August, the San Francisco-based Atomwise, which develops AI systems for drug discovery, signed a research collaboration with pharmaceutical leader Sanofi, potentially worth $1.2 billion. According to a press release, the deal “incorporates deep learning for structure-based drug design, enabling the rapid, AI-powered search of Atomwise’s proprietary library of more than 3 trillion synthesizable compounds.” 

Event

MetaBeat 2022

MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.

Register Here

Drug discovery depends on a first step of “hit identification,” where the right molecules – hits – that bind to a target protein and modify its function are identified. According to an August 2020 VentureBeat article, Atomwise claims its AtomNet platform can screen 16 billion chemical compounds for potential hits in under two days, expediting a process that would normally take months or years. 

In 2022, Atomwise also strengthened its management team and bulked up its executive team. It will need that strength in a competitive space that includes Verge Genomics, Certara, Insilico Medicine, Recursion and Benevolent AI.

ClosedLoop AI: Digging into patient data

It’s been a big year for Austin, Texas-based ClosedLoop AI, since raising $34 million in August 2021. The company, which provides a data science platform that enables healthcare organizations to use AI to improve outcomes and reduce costs, was selected to participate in the AWS Healthcare Accelerator for Health Equity, and it won a 2022 Best in KLAS Award for healthcare artificial intelligence. 

Founded in 2017, the ClosedLoop platform provides off-the-shelf AI models and automation workflows for healthcare applications and manual processes involving data science tasks, examining patient data on an individual level and analyzing data points. Healthcare provider organizations have used ClosedLoop to make decisions on medical interventions and preventative measures for issues such as chronic kidney disease or heart failure. 

Top ClosedLoop AI competitors include heavyweights such as DataRobot and Dataiku, as well as Abacus Insights and Jvion. 

Digital Diagnostics: Identifying eye disease

In 2018, Iowa-based Digital Diagnostics made headlines when it became the first autonomous AI system authorized by the U.S. Food and Drug Administration. 

But 2022 has been kind to the company, whose AI-diagnostic system, the IDx-DR, can be used to identify diabetic retinopathy –- one of the leading causes of blindness in the U.S. and other developed countries –- as well as other serious eye diseases, including macular edema. In August, Digital Diagnostics announced that it had raised $75 million, one of the largest healthcare tech funding rounds this year. 

“There’s a strong mission and purpose for us to get our technology to patients that really need to be tested, and certainly to providers that may be burnt out or are getting burnt out,” Seth Rainford, cofounder, president and COO of Digital Diagnostics, recently told VentureBeat.

Cleerly: AI for cardiac imaging

New York-based Cleerly has been on a mission to transform cardiac care since its founding in 2017. It has enjoyed a huge 2022, raising a fresh round of $192 million in July for its AI-based approach to translate advanced imaging science into a new approach for identifying people at risk of heart attacks. 

According to a company press release, the research that evolved into Cleerly’s technologies was conducted in The Dalio Institute for Cardiovascular Imaging at the New York-Presbyterian Hospital and Weill Cornell Medicine, including large-scale clinical trials with more than 50,000 patients. It comprised the most extensive body of coronary imaging research to study how imaging can be used to better understand heart disease and project patient outcomes. 

A February 2022 study published in the Journal of American College of Cardiology found Cleerly’s AI platform is “as good or better than invasive angiography” – helping to catch heart disease early, before patients begin to show symptoms. 

Owkin: Finding the right drug for every patient

Talk about a big 2022: The medical-AI unicorn Owkin secured $80 million in June from pharmaceutical leader Bristol Myers Squibb as the two companies partner on drug trials.

The French-American, New York-based startup, founded in 2016, has developed a federated learning–based technology to speed up drug discovery and development, drawing on health data that is typically siloed, such as from U.S. and European hospitals.

Last week, Owkin announced two first-ever AI diagnostics approved for use in Europe. The first can predict whether a breast cancer patient will relapse after treatment, while the other can identify a biomarker that opens up potentially life-saving treatment for colorectal cancer patients.

Deepcell: AI for cell biology research

Founded in 2017, Menlo Park, CA-based Deepcell, which was spun out of Stanford University, raised fresh funds in March to use artificial intelligence to find new ways to understand biology. 

Back in 2020, Deepcell cofounder and CEO Maddison Masaeli told VentureBeat that Deepcell’s AI-powered approach “is able to differentiate among cell types with greater accuracy than traditional cell isolation techniques that rely on antibody staining or similar methods.” 

And in a February 2022 interview, Masaeli explained that the Deepcell platform relies on deep neural nets as the “ultimate cell classifier,” so that the model “learns continuously from the images that are collected.” Currently, that includes around 1.5 billion images. 

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.

Repost: Original Source and Author Link

Categories
Security

0ktapus phishing campaign has attacked over 130 companies

Over 130 organizations, including Twilio, DoorDash, and Cloudflare, have been potentially compromised by hackers as part of a months-long phishing campaign nicknamed “0ktapus” by security researchers. Login credentials belonging to nearly 10,000 individuals were stolen by attackers who imitated the popular single sign-on service Okta, according to a report from cybersecurity outfit Group-IB.

As Group-IB goes on to detail, the attackers used that access to pivot and attack accounts across other services. On August 15th, the secure messaging service Signal alerted users that the attackers’ Twilio breach allowed them to reveal as many as 1,900 Signal accounts and confirmed they were able to register new devices to the accounts of a few, which would allow the attackers to send and receive from that account. This week Twilio also updated its breach notification, noting that 163 customers had their data accessed. It also noted that 93 users of Authy, its cloud service for multifactor authentication, had their accounts accessed and additional devices registered.

Targets of the phishing campaign were sent text messages that redirected them to a phishing site. As the report from Group-IB states, “From the victim’s point of view, the phishing site looks quite convincing as it is very similar to the authentication page they are used to seeing.” Victims were asked for their username, password, and a two-factor authentication code. This information was then sent to the attackers.

Interestingly, Group-IB’s analysis suggests that the attackers were somewhat inexperienced. “The analysis of the phishing kit revealed that it was poorly configured and the way it had been developed provided an ability to extract stolen credentials for further analysis,” Roberto Martinez, a senior threat intelligence analyst at Group-IB, told TechCrunch.

But inexperienced or not, the scale of the attack is massive, with Group-IB detecting 169 unique domains targeted by the campaign. It’s believed that the 0ktapus campaign began around March 2022 and that so far, around 9,931 login credentials have been stolen. The attackers have spread their net wide, targeting multiple industries, including finance, gaming, and telecoms. Domains cited by Group-IB as targets (but not confirmed breaches) include Microsoft, Twitter, AT&T, Verizon Wireless, Coinbase, Best Buy, T-Mobile, Riot Games, and Epic Games.

Cash appears to be at least one of the motives for the attacks, with researchers stating, “Seeing financial companies in the compromised list gives us the idea that the attackers were also trying to steal money. Furthermore, some of the targeted companies provide access to crypto assets and markets, whereas others develop investment tools.”

Group-IB warns that we likely won’t know the full scale of this attack for some time. In order to guard against similar attacks like this, Group-IB offers the usual advice: always be sure to check the URL of any site where you’re entering login details; treat URLs received from unknown sources with suspicion; and for added protection, you can use an “unphishable” two-factor security keys, such as a YubiKey.

This recent string of phishing attacks is one of the most impressive campaigns of this scale to date, according to Group-IB, with the report concluding that “Oktapus shows how vulnerable modern organizations are to some basic social engineering attacks and how far-reaching the effects of such incidents can be for their partners and customers.”

The scale of these threats isn’t likely to decrease any time soon, either. Research from Zscaler shows that phishing attacks increased by 29 percent globally in 2021 compared to the previous year and notes that SMS phishing in particular is increasing faster than other kinds of scams as people have started to better recognize fraudulent emails. Socially engineered scams and hacks were also seen rising during the COVID-19 pandemic, and earlier this year, we even saw that both Apple and Meta shared data with hackers pretending to be law enforcement officials.

Correction August 26th, 2:26PM ET: An earlier version of this story included Signal as one of the companies targeted and compromised by the phishing attacks. It was not one of the victims with security breached by the attackers through phishing. The attackers breached Twilio, which handles text messaging for phone number verifications, and were able to register new devices to the accounts of Signal users without having access to Signal directly. We regret the error.

Update August 26th, 2:26PM ET: Added updated breach information from Twilio noting Authy accounts accessed.

Repost: Original Source and Author Link

Categories
AI

Why some AI companies are securing massive funding despite economic downturn

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Watch here.


Tech startups are going through tough times as a result of a slowdown in growth capital. Investment firms are advising their portfolio companies to extend their runway. Companies are suffering from valuation markdowns and resorting to layoffs to cut costs. 

The artificial intelligence (AI) market is no exception. The CB Insights State of AI report for Q2 2022 shows global funding for AI startups dropped for the third consecutive quarter with a 21% decrease quarter-over-quarter. Mega-round fundings (i.e., rounds of more than $100 million) have seen a 33% drop quarter-over-quarter and only 12 new AI unicorns were born, the lowest since Q4 2020.

At the same time, the market has seen a 116% increase in exits – 90% of which are mergers and acquisitions, indicating that startups are gravitating toward large and financially stable companies as they continue to face cash problems.

However, amid the economic downturn, some AI startups have had no trouble raising huge investment rounds. And they hint at where the AI market might be headed in the near future.

Research labs led by AI celebrities are hot

Among the recipients of top equity deals in 2022 are AI research labs Anthropic ($580 million in series B) and Inflection AI ($225 in venture capital).  

Event

MetaBeat 2022

MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.

Register Here

Anthropic’s website describes the lab as “an AI safety and research company that’s working to build reliable, interpretable and steerable AI systems.” It further says that it aims to address the unpredictability, unreliability and opacity of current AI systems. The company acknowledges that it’s currently focused on research with foreseeable opportunities to “create value commercially and for public benefit.” Since its founding in 2021, the company has released several research papers on transformer neural networks, large language models (LLMs) and reinforcement learning. 

That, by itself, doesn’t sound like a convincing pitch to make during an economic downturn. But perhaps what makes Anthropic interesting is that it was cofounded by Dario Amodei, the former VP of research at OpenAI.

After the $580 million fundraise in April, Amodei declared that the company will “explore the predictable scaling properties of machine learning systems, while closely examining the unpredictable ways in which capabilities and safety issues can emerge at scale.”

Research on safety and interpretability are crucial to the application of AI in the real world. But it’s also expensive, especially when it is applied “at scale” as Anthropic aims to do. Large-scale machine learning models are expensive to train and run, which suggests that Anthropic will soon need to raise more capital or find a large tech company that can monetize its technology. 

Inflection AI, the other research lab that has secured a megadeal, presents itself as “an AI-first company, redefining human-computer interaction.” Inflection aims to leverage recent advances in AI to develop the “ability to relay our thoughts and ideas to computers using the same natural, conversational language we use to communicate with people.”

This suggests that the company will be focused on LLMs, an exciting and costly area of research that still has many challenges to solve. The company was cofounded by Mustafa Suleyman, cofounder of DeepMind, and Reid Hoffman, cofounder of LinkedIn. The company has also recently recruited AI scientists from Google and Meta, according to CNBC.

Inflection launched in March with $225 million in funding from Greylock Partners, a VC firm that counts Suleyman and Hoffman as its partners. Given the costs of research and talent the company is facing, this probably won’t be the last we hear of it securing megadeals.

Healthcare, fintech and retail AI startups still raising funding

There is no shortage of ideas to apply AI to real-world applications. But during the downturn, areas of applied AI with more promising results continued to raise funding while others stagnated.

According to the CB Insights report, retail tech AI funding increased 24% in Q2 2022, nearing its pre-downturn levels. The biggest winner was Faire, which raised two rounds of extension to its series G funding, totaling $596 million. 

Faire is a marketplace that connects indie brands with local retailers that can sell their goods. It uses machine learning at different levels of its platform, including matching the supply-and-demand side of the market, helping brands better present their catalogs and profiles, optimizing search and recommendations for retailers and managing risk.  

Funding in healthcare AI decreased by 20% in Q2 2022 but is still doing much better than many other sectors. The biggest deal went to Biofourmis, which raised $300 million in series D. Biofourmis uses machine learning to monitor patients and predict diseases. The company uses hardware sensors paired with FDA-approved software that continually analyzes biomarkers, like heart rate, temperature and respiration rate. Predictive models have much potential to improve patient health and reduce the costs of care.

Fintech AI has managed to maintain its funding levels. The biggest deal went to Germany-based Taxfix, which nabbed $220 million in series D. Taxfix is a mobile assistant for tax returns. Users give the app a snapshot of their payslip and fill out a few additional details. The app provides them with their tax situation and estimated refund. For a premium, the app will also file taxes on the user’s behalf. The company uses machine learning and rule-based AI to automate the process of filling out tax forms and filing taxes. With its growing user base, the company, valued at $1 billion after the new round of funding, will now focus on expanding to new markets and creating new products to extend its touch points with customers beyond tax season.

Tricky times for AI startups

As capital becomes scarce, AI startups that are venturing into uncharted lands will find it harder to get funding. AI luminaries seem to be the exception to the rule, and they will continue to attract investors who have room to wait for long-term returns on investments.

AI companies that have already established their product/market fit and have a solid user base will also have a greater chance of raising funding during the downturn, as investors will be looking for startups that are ready for aggressive growth and, given enough capital, can shortcut their path to profitability.

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn more about membership.

Repost: Original Source and Author Link

Categories
AI

Smartling lands $160M to help companies translate their content automatically

Join gaming leaders, alongside GamesBeat and Facebook Gaming, for their 2nd Annual GamesBeat & Facebook Gaming Summit | GamesBeat: Into the Metaverse 2 this upcoming January 25-27, 2022. Learn more about the event. 


As the pandemic drives businesses online, translation is becoming a key part of the digital transformation equation. One large-scale behavioral study in 2014 showed that 75% of consumers are more likely to buy products from websites in their native language. Another, this one by Localize, found businesses that invested in translation were 1.5 times more likely to observe an increase in revenue.

Against this backdrop, Smartling, a self-described cloud translation company, has raised $160 million in a venture capital round led by Battery Ventures. CEO Jack Welde says that the proceeds will be used to expand Smartling’s headcount while supporting product development and marketing efforts.

Smartling, which was founded in 2009 by Welde and Andrey Akselrod, is a language translation company that enables customers to localize content across devices and platforms. Smartling leverages a combination of AI-powered translation tools and human translators, localizing content for particular markets to ensure its intended meaning and connotation remains the same — and isn’t misunderstood.

“Two truisms have emerged about today’s enterprises: all business is global, and content drives global business,” Welde said in a statement. “The third leg of that stool is translation, since nearly all customers want to buy in their own language. This is a tremendous opportunity, and we are excited to realize it together with Battery.”

Localizing content

Smartling uses automation to quickly translate content into different languages. New content on customer sites and apps is flagged for translation and sent to translators for rewriting; when changes to the original language are detected, all foreign-language versions are flagged for translation. The changes are then delivered to front-end users through the backend of a customer’s system, independent of app updates.

In 2017, Smartling launched a mobile delivery network designed to deliver updated translations to smartphone apps decoupled from updates to the app’s core code. The idea is that international users see translated content faster without having to update the app beforehand. Instead, updates and new translations can appear as soon as the user opens the app.

Smartling claims to work with a few thousand translators in addition to an in-house staff of about 160 to provide text and video translation services. Translators perform their work in a computer-aided translation tool, which is followed by a translation review, legal review, and editing process.

Smartling relies partially on machine translation — i.e., AI-powered translation — for “high volume, low priority” content translations. While generally accurate, studies show that machine translation systems can produce text that’s less “lexically” rich than human translations — and more prejudicial. Google recently identified (and claims to have addressed) gender bias in the translation models underpinning Google Translate, particularly with regard to resource-poor languages like Turkish, Finnish, Persian, and Hungarian.

We’ve reached out to Smartling for more information about its AI bias mitigation efforts and will update this article if we hear back.

Opportunity for growth

In a boon for Smartling, the market for online translation services continues to climb steeply upward. According to Statista, it’s doubled in size from 2009 to 2019, reaching $49.6 billion two years ago. The machine translation market alone could be worth $230.67 in the next five years, Mordor Intelligence projects, growing at a compound annual growth rate of 7.1% from 2021 to 2026.

Underlining the opportunity, over 361 million people around the world participate in cross-border ecommerce. A study by Standard Chartered found that nearly half of U.S. businesses today say that their best growth opportunity is outside the U.S. And according to Common Sense Advisory, 76% of buyers say that they prefer to purchase a product with information in their own language when faced with the choice of two similar products.

Smartling has competition in Language I/O, a startup providing AI technologies for real-time, company-specific language translations. Unbabel and Lilt are among other rivals in the segment. But Smartling has managed to attract “hundreds” of large business-to-business and business-to-consumer customers including InterContinental, Pinterest, Shopify, and SurveyMonkey.

“Enterprises generally succeed on the strength of technology, supply chains, people, and workflows. As content has become essential to go-to-market strategies, content distribution has in some sense become its own supply chain and workflow. And, as that content supply chain extends globally, translation at scale has become the critical last mile for global enterprise growth,” Battery Ventures general partner Morad Elhafed said in a press release.

Smartling has raised over $220 million in venture capital to date.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Repost: Original Source and Author Link

Categories
AI

Europe’s AI laws will cost companies a small fortune – but the payoff is trust

Hear from CIOs, CTOs, and other C-level and senior execs on data and AI strategies at the Future of Work Summit this January 12, 2022. Learn more


Artificial intelligence isn’t tomorrow’s technology — it’s already here. Now too is the legislation proposing to regulate it.

Earlier this year, the European Union outlined its proposed artificial intelligence legislation and gathered feedback from hundreds of companies and organizations. The European Commission closed the consultation period in August, and next comes further debate in the European Parliament.

As well as banning some uses outright (facial recognition for identification in public spaces and social “scoring,” for instance), its focus is on regulation and review, especially for AI systems deemed “high risk” — those used in education or employment decisions, say.

Any company with a software product deemed high risk will require a Conformité Européenne (CE) badge to enter the market. The product must be designed to be overseen by humans, avoid automation bias, and be accurate to a level proportionate to its use.

Some are concerned about the knock-on effects of this. They argue that it could stifle European innovation as talent is lured to regions where restrictions aren’t as strict — such as the US. And the anticipated compliance costs high-risk AI products will incur in the region – perhaps as much as €400,000 ($452,000) for high risk systems, according to one US think tank — could prevent initial investment too.

So the argument goes. But I embrace the legislation and the risk-based approach the EU has taken.

Why should I care? I live in the UK, and my company, Healx, which uses AI to help discover new treatment opportunities for rare diseases, is based in Cambridge.

This autumn, the UK published its own national AI strategy, which has been designed to keep regulation at a “minimum,” according to a minister. But no tech company can afford to ignore what goes on in the EU.

EU General Data Protection Regulation (GDPR) laws required just about every company with a website either side of the Atlantic to react and adapt to them when they were rolled out in 2016. It would be naive to think that any company with an international outlook won’t run up against these proposed rules too. If you want to do business in Europe, you will still have to adhere to them from outside it.

And for areas like health, this is incredibly important. The use of artificial intelligence in healthcare will almost inevitably fall under the “high risk” label. And rightly so: Decisions that affect patient outcomes change lives.

Mistakes at the very start of this new era could damage public perception irrevocably. We already know how well-intentioned AI healthcare initiatives can end up perpetuating structural racism, for instance. Left unchecked, they will continue to.

That’s why the legislation’s focus on reducing bias in AI, and setting a gold standard for building public trust, is vital for the industry. If an AI system is fed patient data that does not accurately represent a target group (women and minority groups are often underrepresented in clinical trials), the results can be skewed.

That damages trust, and trust is crucial in healthcare. A lack of trust limits effectiveness. That’s part of the reason such large swathes of people in the West are still declining to get vaccinated against COVID. The problems that’s causing are plain to see.

AI breakthroughs will mean nothing if patients are suspicious of a diagnosis or therapy produced by an algorithm, or don’t understand how conclusions have been drawn. Both result in a damaging lack of trust.

In 2019, Harvard Business Review found that patients were wary of medical AI even when it was shown to out-perform doctors, simply because we believe our health issues to be unique. We can’t begin to shift that perception without trust.

Artificial intelligence has proven its potential to revolutionize healthcare, saving lives en route to becoming an estimated $200 billion industry by 2030.

The next step won’t just be to build on these breakthroughs but to build trust so that they can be implemented safely, without disregarding vulnerable groups, and with clear transparency, so worried individuals can understand how a decision has been made.

This is something that will always, and should always, be monitored. That’s why we should all take notice of the spirit of the EU’s proposed AI legislation, and embrace it, wherever we operate.

Tim Guilliams is a co-founder and CEO of drug discovery startup Healx.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Repost: Original Source and Author Link

Categories
AI

Report: Companies that invested in automation saw 5% to 7% revenue increase

Hear from CIOs, CTOs, and other C-level and senior execs on data and AI strategies at the Future of Work Summit this January 12, 2022. Learn more


New research from SnapLogic and Cebr found that the U.K. could have prevented £10-£14 billion ($13.4-$18.8 million USD) of its pandemic-related gross domestic product (GDP) contraction if it had matched the automation level of the U.S. Furthermore, the U.S. could have witnessed a $105-$212 billion smaller GDP contraction if it was as automated as Singapore.

The continued adoption of automation across the U.S. and U.K. has helped companies position themselves for growth, while also having the added benefit of improving resilience against economic disruption. Within three months of investment, U.S. companies witnessed an average year-on-year increase in revenue of 7%, or an extra $195 billion per month, and saw an average annual increase in employment of 7%, equating to a total of 7.2 million jobs.

As investment in automation grows, there are certain technologies leading the way. The research finds 78% of U.S. companies directed their investments towards cloud computing, and 71% focused on data integration. The Internet of Things (IoT) and big data analysis were the next most popular technologies in the U.S., with 64% and 62% adoption rates, respectively.

Automation boosts business revenue and economic resilience. The average year-on-year increase in revenue of U.S. companies investing in automation is 195 billion dollars a month. The average year-on-year increase in revenue of UK companies investing in automation is 14 billion per month.

Despite automation commonly being thought of as a way to cut costs, U.S. businesses that automated did so to boost their company’s speed and agility (52%), while improving employee productivity (47%). Automation has helped companies to achieve these goals, with the potential to increase productivity by 15% in the long term, which translates to the creation of approximately 16 million jobs in the U.S, according to the research.

Independent consultancy Cebr surveyed 1,000 businesses in the U.S. and U.K. about their automation strategies, initiatives, and results to develop this study.

Read the full report by SnapLogic and Cebr.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Repost: Original Source and Author Link

Categories
AI

Density, which provides occupancy-tracking sensors to companies, raises $125M

Join gaming leaders online at GamesBeat Summit Next this upcoming November 9-10. Learn more about what comes next. 


New York-based Density, a startup developing people-counting, AI-powered sensors, today announced that it raised $125 million in financing, bringing the company’s valuation to $1.05 billion. The round was led by Kleiner Perkins with participation from 01 Advisors, Upfront Ventures, Founders Fund, and Altimeter Capital. It adds to Density’s existing over $92 million in venture capital, with the total now standing at $225 million.

Density says that it’ll put the funds toward R&D and its ongoing customer acquisition efforts. Alongside the tranche, Density revealed that it acquired HelixRE, a technology that creates a digital representation of buildings to streamline data collection. Density CEO Andrew Farah claims that HelixRE’s technology will help Density to optimize measurement while providing its customers with technology to better design office spaces.

“Density will use the funds to grow its global team and support its rapidly expanding customer base,” Farah told VentureBeat via email. “We’ve grown our employee base by 300% since the start of 2021, with plans to double its headcount in the next calendar year. And we’ve experienced more than 500% growth since March 2020.”

Origins

Farah conceived of Density’s technology while he was in graduate school at Syracuse and working at a mobile app development startup. His initial goal — to measure how busy a popular coffee shop was — led him to explore a couple of solutions before settling on the one that formed the foundation for Density’s people-counting sensors.

Density leverages depth-measuring hardware and an AI backend to perform crowd analytics that overcome the challenges posed by corners, hallways, doorways, and conference rooms. Customers use its stack to figure out which parts of their offices get the most and least use and deliver people-counting metrics to hundreds and even thousands of employees.

One of Density’s apps, Portfolio, draws on sensor data to show real-time, day-over-day “return to office” insights for health compliance purposes. Portfolio automatically records weekly occupancy and usage changes and enables users to set safe maximum capacities based on local, pandemic-specific requirements. Beyond this, the software surfaces data over time to enable companies to “right-size” — i.e., upscale or downscale — their office layouts.

Density Open Area

Above: Density’s Open Area sensor.

Image Credit: Density

Density last year launched Open Area, a sensor that uses machine learning and radar to track workspace usage. More capable than Density’s previous sensors, Open Area detects key points on people’s bodies that the device translates in software to point clouds on a 3D graph. For instance, when positioned above a desk where people are seated, Open Area can show the rough outline of those people as they come and go.

Earlier this year, Density acquired Nashi, which provided space- and desk-reservation capabilities for employees working both at home and in the office. In October, after rebranding Nash’s software Workplace by Density, Density rolled out Heatmaps, a feature that visualizes where people spend time on a floor plan.

In the future, Farah says that HelixRE’s technology will enable Density to combine digital images of an environment with real-time data capture from the Density platform. On its website, HelixRE says it leverages a combination of photogrammetry, computer vision, AI, and cloud computing to convert raw captured data — including 360-degree photos and lidar-based measurements — into building plans.

“The emergence of hybrid work, post-pandemic, has fundamentally changed the nature and purpose of our buildings,” Farah said in a statement. “Over the next five years, the vast majority of the built world will be instrumented for measurement. This new infrastructure will generate reliable, real-time utilization data; it will support the dynamic needs of hybrid work; and help designers, architects, and real estate and workplace teams improve the environment and spaces we use each day.”

Tracking technologies

The pandemic initially hurt Density’s sales because many of the company’s customers temporarily shut down. But since the close of its series B funding in June 2018, Density says that its sensors have counted more than 150 million people in dozens of countries across 1.25 billion square feet.

Density

While pitched as workplace analytics and safety products, some privacy experts worry that technologies like Density’s will normalize greater levels of surveillance — capturing data about workers’ movements and allowing managers to chastise employees in the name of productivity. In the U.K., more than one in seven employees have reported that monitoring by their employer has increased since the pandemic began. The response has been predictably negative. Of the remote or hybrid workers surveyed in a recent ExpressVPN report, 59% said that they felt stress as a result of their employer monitoring them — and more than half said they’d quit if their manager implemented surveillance measures.

But Farah insists that Density’s platform is privacy-preserving. He points out that the sensors can’t determine the gender or ethnicity of the people that they track, for example, nor perform facial recognition. Moreover, Density stores all data on U.S.-based servers, he says, and allows customers to export and permanently delete data linked to their account.

“Unlike cameras, the GDPR-compliant sensors we’ve developed are anonymous by design. They can’t capture any personally identifiable information, and no data captures leave the sensors during normal operations,” Density writes on its website. “Density automatically expires data from visitors that have not been seen in nine months.”

Density’s clients include Fortune 10 companies like Uber, Shopify, Okta, Splunk, VMWare, and Cisco as well as “high-growth” ventures like Okta, a publicly traded identity and access management company based in San Francisco. In anticipation of further expansion, Density has added a number of new executives to its roster, including a chief revenue officer and workplace innovation lead.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Repost: Original Source and Author Link

Categories
AI

Neuro-ID tracks user behavioral data to help companies boost conversion

Neuro-ID, a Montana-based company offering software to combat online fraud and increase conversion rates through behavioral data and analytics, announced that it has raised $35 million.

Neuro-ID says it helps brands in a variety of industries that have significant digital transactions, including Intuit, Square, Affirm, OppFi, and Elephant Insurance. In some cases, the company says it has helped these companies increase conversion by 200% and reduce historical fraud rates by 35%.

Expanding on the company’s technology and the leverage it provides to technical decision-makers, CEO Jack Alton told VentureBeat that Neuro-ID’s “Human Analytics JavaScript” service sits behind digital interactions and in real-time translates the taps, types, and swipes of digital users into actionable insight. For example, when a new user is signing up for a merchant account, Neuro-ID looks at the actual timing of the signup, frequency of interaction — including changes to personal information — and the user’s timeline of activities.

Alton noted that this provides a valuable new view into the human behind the screen — enabling the company’s clients to better understand the risk and opportunity of onboarding new customers.

New visibility dimension into customer analytics

Sharing further on how Neuro-ID is differentiated from its key competitors in the behavioral analytics and security space, Alton said, “Traditional behavioral analytics companies like NuData have used behavioral technology to do things like authenticate existing customers to prevent account takeovers by malicious actors. Neuro-ID is focused on tackling a much larger ‘conversion crisis’ that all digital organizations face.”

“For the past decade, 90% of all digital onboarding journeys have continued to result in frustration or failure. This has frustrated executives and led to endless a/b testing as organizations try to understand why so many people start and end up abandoning their onboarding journey,” he added.

Behavioral strategy plays a key role in today’s corporate strategy and decision-making processes, as highlighted in this article from Mckinsey. Neuro-ID says its proprietary “Friction Index” dashboard tries to identify the root cause of friction while screening for fraud attacks.

The funding for the software company came from Canapi Ventures and existing investors Fin VC and TTV Capital. The announcement was made in a recent press release.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Repost: Original Source and Author Link

Categories
AI

Infrastructure and data issues hamper companies adopting AI, study finds

More than three-quarters of companies say that they have AI models that never come into use. For 20% of companies, the numbers look even worse, with only 10% of their models making it into production.

That’s according to a new survey commissioned by Run:AI, which found that infrastructure challenges are causing resources to sit idle at companies investing in AI. “[I]f most AI models never make it into production, the promise of AI is not being realized,” Run:AI CEO Omri Geller said in a statement. “Our survey revealed that … data scientists are requesting manual access to GPUs, and the journey to the cloud is ongoing.”

The research conducted by Global Surveyz canvassed more than 200 scientists, AI and IT practitioners, and system architects across companies with over 5,000 employees. Just 17% of respondents said that they were able to achieve “high utilization” of their hardware resources, while 22% admitted that their infrastructure sits idle for the most part. That’s despite significant investment — 38% of respondents pegged their company’s annual budget for hardware, software, and cloud fees at more than $1 million. For 15%, their companies spend more than $10 million.

Implementation challenges

Many challenges stand in the way of successfully embedding AI throughout an organization. In an Alation whitepaper, a clear majority of employees (87%) cited data quality shortcomings as the reason their organizations failed to embrace the technology. Another report — this from MIT Technology Review Insights and Databricks — found that AI’s business impact is limited by issues in managing its end-to-end lifecycle.

The end result is abysmal adoption rates. According to a 2019 IDC study, only 25% of the organizations already using AI have developed an “enterprise-wide” strategy. A recent Juniper Networks survey is less optimistic, with only 6% of respondents reporting adoption of AI-powered solutions across their business.

In its research, Run:AI identified data inconsistencies as the biggest deployment blocker. Results state 61% of respondents said that data collection, data cleansing, and governance caused deployment problems. Forty-two percent of experts responding to the survey highlighted challenges with their companies’ AI infrastructure and compute capacity. More than a third say they had to manually request access to resources in order to complete their work.

Data scientists spend the bulk of their time cleaning and organizing data, according to a 2016 survey by CrowdFlower. And respondents to Alation’s latest quarterly State of Data Culture Report said that inherent biases in the data being used in their AI systems produce discriminatory results that create compliance risks for their organizations.

The business value of any AI solution is likely to be limited without clean, centralized data pools or a strategy for actively managing them, Broadridge VP of innovation and growth Neha Singh noted in a recent piece. “McKinsey estimates that companies may be squandering as much as 70% of their data-cleansing efforts,” she wrote. “The key is prioritizing these efforts based on what’s most critical to implement the most valuable use cases.”

Despite the hurdles, Run:AI reports that companies still commit to AI. These put millions toward infrastructure and likely millions more toward trained staff. Seventy-four percent of survey respondents said that their employers were planning to increase hardware capacity or infrastructure spend in the near future.

“Companies that handle these challenges the most effectively will bring models to market and win the AI race,” Geller continued.

VentureBeat

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative technology and transact.

Our site delivers essential information on data technologies and strategies to guide you as you lead your organizations. We invite you to become a member of our community, to access:

  • up-to-date information on the subjects of interest to you
  • our newsletters
  • gated thought-leader content and discounted access to our prized events, such as Transform 2021: Learn More
  • networking features, and more

Become a member

Repost: Original Source and Author Link