In the past five years, interest in applying artificial intelligence (AI) approaches in drug research and development (R&D) has surged. Driven by the expectation of accelerated timelines, reduced costs and the potential to reveal hidden insights from vast datasets, more than 150 companies with a focus on AI have raised funding in this period, based on an analysis of the field by Back Bay Life Science Advisors (Figure 1a). And the number of financings and average amount raised soared in 2021. At the forefront of this field are companies harnessing AI approaches such as machine learning (ML) in small-molecule drug discovery, which account for the majority of financings backed by venture capital (VC) in recent years (Figure 1b), as well as some initial public offerings (IPOs) for pioneers in the area (Table 1). Such companies have also attracted large pharma companies to establish multiple high-value partnerships (Table 2), and the first AI-based small-molecule drug candidates are now in clinical trials (Nat.
Greg Nichols covers robotics, AI, and AR/VR for ZDNet. A full-time journalist and author, he writes about tech, travel, crime, and the economy for global media outlets and reports from across the U. A company that uses construction workers as roving cameramen to analyze progress on the job site has secured $60 million in Series C funding. Buildots, whose growth is tracking a broader technological turn in the practically neolithic construction sector, will use the cash to expand its product offering in a bid to be the management suite of choice for construction oversight. Construction accounts for 13% of the world's GDP, but while other traditional industries, like manufacturing, have increased productivity over the years, productivity has remained almost stagnant in the building sector.
During the pandemic especially, it's become overwhelming for small- and medium-sized businesses (SMBs) to answer all of their customer service requests. A Freshworks survey found that companies experienced a 71% increase in overall contact volume between February 2020 and January 2021, and expect it to increase further. At the same time, customers -- while empathetic -- have become more demanding. The same poll shows that 68% of customer service managers have seen an increase in customer expectations. What's a company to do? Automation is one route to more manageable customer experience workloads, potentially.
Deep North, the intelligent video analytics company, announced the launch of Checkout IQ, its new retail loss prevention solution, which uses computer vision and AI to reduce shrinkage at checkout. The release reflects Deep North's ongoing commitment to empower retailers with data-driven tools to keep their businesses competitive, maximize revenue, and offer great customer experiences. With shrinkage at an all-time high and an increase in organized retail crime, Deep North is providing a new way for retailers to prevent fraud loss and improve their bottom line. Raises $10.5 Million Series A to Help CX Teams Turn Conversations Into Insights and Automation Designed to help retailers reduce retail fraud activities, Checkout IQ works with retailers' existing camera systems. By analyzing camera views, the application identifies items that are being scanned by the customer or the cashier, and this count is cross-referenced with the POS item count to detect any discrepancies.
Companies are building software that uses AI to monitor people's behavior and interpret their emotions and body language in real life, virtually and even in the metaverse. But to develop that AI, they need fake data, and startups are stepping in to supply it. Synthetic data companies are providing millions of images, videos and sometimes audio data samples that have been generated for the sole purpose of training or improving AI models that could become part of our everyday lives in controversial forms of AI such as facial recognition, emotion AI and other algorithmic systems used to keep track of people's behavior. While in the past companies building computer vision-based AI often relied on publicly available datasets, now AI developers are looking to customized synthetic data to "address more and more domain-specific problems that have zero data you can actually access," said Ofir Zuk, co-founder and CEO of synthetic data company Datagen. Synthetic data companies including Datagen, Mindtech and Synthesis AI represent a corner of an increasingly compartmentalized AI industry.
"By 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated." This is a prediction from Gartner that you will find in almost every single article, deck or press release related to synthetic data. We are repeating this quote here despite its ubiquity because it says a lot about the total addressable market of synthetic data. Let's unpack: First, describing synthetic data that is "synthetically generated" may seem tautologic, but it is also quite clear: We are talking about data that is artificial/fake and created, rather than gathered in the real world. Next, there's the core of the prediction -- that synthetic data will be used in the development of most AI and analytics projects.
Hugging Face has closed a new round of funding. Following today's funding round, Hugging Face is now worth $2 billion. Lux Capital is leading the round, with Sequoia and Coatue investing in the company for the first time. Some of the startup's existing investors participated once again. These investors include Addition, Betaworks, AIX Ventures, Cygni Capital, Kevin Durant and Olivier Pomel.
Contract lifecycle management (CLM), the method of managing a contract from initiation through award, compliance, and renewal, can be costly for companies. World Commerce and Contracting estimates the average cost of a simple contract at $6,900, rising to over $49,000 for more complex agreements. The opportunity is often worth the investment, but without close contract governance, businesses stand to lose up to 40% of a contract's value, a KPMG survey found. The tantalizing prospect of automating the contracting process has drawn a number of entrepreneurs to the space, including UnitedLex co-founder Ajay Agrawal. Agrawal's newest venture is SirionLabs, which comines AI technologies like natural language processing to import and organize contracts, negotiations, and contract review. Highlighting the investor interest in the segment, SirionLabs announced that it closed an $85 million Series D financing round led by Partners Group with participation from existing investors Sequoia Capital and Tiger Global.
Business intelligence is an increasingly well-funded category in the software-as-a-service market. By handling large amounts of data to analyze and benchmark lines of business, BI promises to help identify, develop and otherwise create new revenue opportunities. Pervasive BI remains elusive, but statistics on the category reveal that about a third of employees use BI tools for analytics to inform strategy. The big data and business analytics market could be worth $684 billion by 2030, according to Valuates Reports, if such outrageously high estimates are to be believed. The segment contains too many vendors to count -- a few include Noogata, Fractal Analytics, Tredence, LatentView and Mu Sigma.