The document provides an overview of artificial intelligence and machine learning, including a history of developments in the field, classifications of different types of AI/ML techniques, and factors contributing to improvements in predictive accuracy. It then discusses applications of AI/ML that are currently in daily use, trends in patenting and M&A activity, and the landscape of venture funding in AI/ML startups, including the most active investors and countries. Key application areas like healthcare, transportation, and agriculture are highlighted.
Otite Média Aguda e Otite Média Com Efusão (Serosa)Dario Hart
Seminário de Otite Médias Agudas e Disfunções da Tuba Auditiva do Hospital Federal de Bonsucesso - Rio de Janeiro
Abordagem Anatomofisiológica, Semiológica, Diagnóstica e Terapêutica
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/introduction-to-the-csi-2-image-sensor-interface-standard-a-presentation-from-the-mipi-alliance/
Haran Thanigasalam, Camera and Imaging Consultant to the MIPI Alliance, presents the “Introduction to the MIPI CSI-2 Image Sensor Interface Standard” tutorial at the May 2023 Embedded Vision Summit.
By taking advantage of select features in standardized interfaces, vision system architects can help reduce processor load, cost and power consumption while gaining flexibility to source components from multiple vendors. In this presentation, Thanigasalam introduces the standardized MIPI CSI-2 imaging conduit solution for interfacing image sensors to processors.
Thanigasalam explains how the solution supports basic operations of a camera sensor, including physical frame transport options and orthogonal commands for autoexposure, autofocus, auto white balance and event detection. He also introduces command sets to help bring up and tune sensors. In addition, Thanigasalam explores provisions to alleviate RF emissions, enable aggregation of data from multiple remote sensors and alleviate the need for dual voltage signaling to avoid electrical overstress issues. He also touches on emerging support for frame transport using WiFi.
Otite Média Aguda e Otite Média Com Efusão (Serosa)Dario Hart
Seminário de Otite Médias Agudas e Disfunções da Tuba Auditiva do Hospital Federal de Bonsucesso - Rio de Janeiro
Abordagem Anatomofisiológica, Semiológica, Diagnóstica e Terapêutica
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/introduction-to-the-csi-2-image-sensor-interface-standard-a-presentation-from-the-mipi-alliance/
Haran Thanigasalam, Camera and Imaging Consultant to the MIPI Alliance, presents the “Introduction to the MIPI CSI-2 Image Sensor Interface Standard” tutorial at the May 2023 Embedded Vision Summit.
By taking advantage of select features in standardized interfaces, vision system architects can help reduce processor load, cost and power consumption while gaining flexibility to source components from multiple vendors. In this presentation, Thanigasalam introduces the standardized MIPI CSI-2 imaging conduit solution for interfacing image sensors to processors.
Thanigasalam explains how the solution supports basic operations of a camera sensor, including physical frame transport options and orthogonal commands for autoexposure, autofocus, auto white balance and event detection. He also introduces command sets to help bring up and tune sensors. In addition, Thanigasalam explores provisions to alleviate RF emissions, enable aggregation of data from multiple remote sensors and alleviate the need for dual voltage signaling to avoid electrical overstress issues. He also touches on emerging support for frame transport using WiFi.
What new developments and capabilities we'll be seeing by the end of 2023 and 2024 in AI. Multimodal AI can make video, control robots. Techniques for amplicifaction and distillation improves quality from little data. Brains can be decoded with AI. What future do we want to create with this power?
Virginia Dignum – Responsible artificial intelligenceNEXTConference
As Artificial Intelligence (AI) systems are increasingly making decisions that directly affect users and society, many questions raise across social, economic, political, technological, legal, ethical and philosophical issues. Can machines make moral decisions? Should artificial systems ever be treated as ethical entities? What are the legal and ethical consequences of human enhancement technologies, or cyber-genetic technologies? How should moral, societal and legal values be part of the design process? In this talk, we look at ways to ensure ethical behaviour by artificial systems. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems. We will in particular focus on the ART principles for AI: Accountability, Responsibility, Transparency.
-Apresentar a Associação Brasileira Pela Continência BC Stuart aos membros da ACSP
- Levar informação acerca do problema (incontinência urinária), problema que afeta mais de 10 milhões de brasileiros.
- Falar sobre as possibilidades de tratamentos
What new developments and capabilities we'll be seeing by the end of 2023 and 2024 in AI. Multimodal AI can make video, control robots. Techniques for amplicifaction and distillation improves quality from little data. Brains can be decoded with AI. What future do we want to create with this power?
Virginia Dignum – Responsible artificial intelligenceNEXTConference
As Artificial Intelligence (AI) systems are increasingly making decisions that directly affect users and society, many questions raise across social, economic, political, technological, legal, ethical and philosophical issues. Can machines make moral decisions? Should artificial systems ever be treated as ethical entities? What are the legal and ethical consequences of human enhancement technologies, or cyber-genetic technologies? How should moral, societal and legal values be part of the design process? In this talk, we look at ways to ensure ethical behaviour by artificial systems. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems. We will in particular focus on the ART principles for AI: Accountability, Responsibility, Transparency.
-Apresentar a Associação Brasileira Pela Continência BC Stuart aos membros da ACSP
- Levar informação acerca do problema (incontinência urinária), problema que afeta mais de 10 milhões de brasileiros.
- Falar sobre as possibilidades de tratamentos
Artificial Intelligence is the new computer of technology. In simple words, AI gives life to the machines—by giving them intelligence. This enables the machine to imitate humans in terms of perception, decision making, speech recognition, and language interpretation. And the way we can construct Ai is through Machine learning.
This PPT is about AI 100 Startups all over the world based on "The AI 100 -CB insights".
In this research paper, you can find each capital, scale, general info(ref: CB Insights), and features.
5 Amazing Examples of Artificial Intelligence in Actionvenkatvajradhar1
As scientists and researchers are desperately trying to transform Artificial Intelligence (AI) into the mainstream, this ingenious technology is already making its way into our daily lives and perpetuating many industry verticals
Artificial Intelligence is trendy. Every event, every strategy meeting and every consulting firm talks about it. This whitepaper aims to separate actual facts and important background information from the overarching marketing buzz.
You will get a short but information-rich wrap up about: What causes the current hype? Where are we today? What are the innovation leaders doing with AI? And what are immediate action points to focus on by applying artificial intelligence to your business?
Silicon Valley Meets Zurich - Mobile Industry Trends From the ValleyRaj Singh
Event based in Zurich discussing differences between the Silicon Valley Tech ecosystem and Zurich. This presentation focused on mobile (investor) trends in the valley.
Executive Summary Part 3 -- Who's Winning the Artificial Intelligence Race be...Paul Schulte
In the spirit of collaboration, I am releasing part 3 of the executive summary (of our 560 page report comparing the big 5 in China and the big 5 in the US).
Part 3 looks first at the internal direction of R&D for each company. US firms are focusing on language, data anlytics and robotics. In a dramatic contrast, Chinese firms are focusing on financial applications, blockchain and computing. Then it looks at the patterns of external M&A. US firms are focusing on consolidating monopoly positions as well as physical assets such as Motorola, Nokia. Why? Chinese firms are acquiring lifestyle companies. Third, we look at the excess cash flow for M&A for tech companies (and market cap to use stock) and the paucity of cash flow for banks. Are banks simply running out of cash flow to buy or build a viable future? Lastly, we do a detailed credit analysis of all companies. Interesting results. Baidu’s credit data are deteriorating at the fastest rate.
To receive the full 560 report, send your email to paul@schulte-research.com. I personally hired several exceptionally talented students from UST and USC. Please support our students -- and pay them a superior wage. They are our future. I am available to go through the entire report in a 90 minute consultation.
Solve for X with AI: a VC view of the Machine Learning & AI landscapeEd Fernandez
What you'll get from this deck
1. The M&A race for AI: by the numbers
2. Watch out! hype ahead: definitions & disclaimers
3. Machine Learning drivers: why is Machine Learning a ‘thing’ now (vs before)
4. Venture Capital: forming an industry, the AI/ML landscape
5. The One Hundred (+13) AI startups to watch in the Enterprise
6. The great Enterprise pivot: applying Machine Learning at scale
7. - where to go next -
Artificial intelligence (AI), also known as machine intelligence, is an aspect of computer science that deals will the designing of intelligent mechanical systems that work and react like humans. AI incorporates information from everything ranging from Google search algorithms to machinal processes. From SIRI to self-driving cars, everything is the outcome of artificial intelligence, which is rapidly progressing and taking over our human lives.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Deepdive in AIML venture landscape By Ajit Nazre Rahul Garg
1. A Deep Dive in the Venture Landscape of
Artificial Intelligence and Machine Learning
September 2015
Ajit Nazre
Rahul Garg
2. Artificial Intelligence Evolution
Artificial Intelligence is on its 3rd reincarnation since its first birth in 1950 and looks like it has
longevity this time around
1950 -1970s – Start of
AI as a concept but no
real applications
1980 -2000 – AI/ML
mainly used in Military &
Academia
2005 onwards – Large tech companies such as IBM, Microsoft, Google, and Facebook have
invested in AI/ML for commercial applications
1956
John McCarthy
organized a
conference at
Dartmouth &
named the field as
Artificial Intelligence
1950
Alan Turing
published a paper
about the possibility
of machines with
true intelligence
1995
US Department of
Defense uses
predator UAV in
Balkan War
1997
IBM’s Deep Blue
wins chess against
World Champion
Gary Kasparov
2011
Debut of Virtual
personal assistants
like Apple’s SIRI &
Microsoft’s Cortana
2011
IBM Watson
computer defeats
Jeopardy game
show champions
Jan 2014
DeepMind team
uses deep learning
algorithms to create
a program that wins
Atari games
Oct 2013
Vicarious breaks any
‘Captcha’ passing
the Turing test
Jun 2015
Facebook launches
Moments that
detects faces and
shares photos with
friends to whom
they belong
May 2015
Google self driving
cars complete 1M
miles autonomously
Jun 2015
DeepMind teaches
program how to
read
3. Artificial Intelligence / Machine Learning Classification
Artificial
Intelligence
Deduction,
Reasoning,
Problem Solving
Knowledge
Representation
Planning Perception:
Computer Vision
Machine
Learning
Robotics: Motion
and
Manipulation
Natural Language
Processing
Social
Intelligence
Supervised Learning Unsupervised
Learning
Reinforcement
Learning
Decision
Tree
Learning
Association
Rule
Learning
Neural
Networks
Inductive
Logic
Programming
Support
Vector
Machines
Bayesian
Networks
Similarity
and Metric
Learning
Clustering
Deep
Learning
Manifold
Learning
Sparse
Dictionary
Learning
Genetic
Algorithms
4. Multiple Factors contributing to Dramatic Improvement in
Prediction Accuracy
Increasing Prediction
Accuracy of
Algorithms
=
Improved Decision
Making
Increase in
affordable
Compute
Power
Big Data
Faster
networks
Cloud Infra-
structure
Sensor
Networks
Advances in
Neuroscience
“Whenever we can replace human judgment by a formula, we should at least consider it.” -
Daniel Kahneman (2002 Nobel Prize in Economics)
5. Applications of AI/ML in Daily Use Already
Info
Search engines
Sentiment analysis (or
opinion mining)
Information Retrieval
Spam filtering for email
Speech and handwriting
recognition
Spoken language
understanding
Stock analysis
Structural health
monitoring
Syntactic pattern
recognition
Topic spotting: categorize
news articles
Weather prediction
Tools
Face Detection
Finance – Derivatives
Trading
Game playing
Software Testing
Internet fraud detection
Machine translation
Medical diagnosis
Mood analysis
Brain machine interface
in prosthetics
Optical character
recognition
Recommendation
systems
Robot locomotion
Services
Advertising - Targeting
Bioinformatics
Automatic word completion
Chemical Informatics
Classifying DNA Sequences
Computer Vision – Object
Recognition
Customer Segmentation
Detecting Credit Card Fraud
6. R&D Activity in AI / ML as measured by Patents granted
Source: MarketRealist.com
IBM and Microsoft had more patents in AI / ML granted in 2014 than all others
7. M&A Activity in AI / ML is Heating up
Google
Dark Blue Labs, Vision Factory, Jetpac, Quest Visual, Titan
Aerospace, Deepmind Technologies, Boston Dynamics, Bot
& Dolly, Holomni, Redwood Robotics, Industrial perception,
Schaft, Flutter, Wavii, Behavio, DNNresearch, Viewdle,
Pittpatt, Saynow, Phonetic Arts, Metaweb
21
10
6 6
4
0
5
10
15
20
25
Google Facebook Yahoo Apple IBM
Facebook
Pebbles, Surreal Vision, Ascenta, QuickFire,
Wit.ai, Oculus VR, SportStream, Jibbigo,
Face.com, RecRec
Yahoo
Tomfoolery, Cloud Party, Skyphrase, LookFlow,
IQ Engines, Qwiki
Apple
Metaio, Cue, Novauris Technologies, Polar
Rose, Siri, FingerWorks
IBM
AlchemyAPI, Silverpop Systems, Curam
Software, Languagae Analysis Systems
No. of companies acquired in AI/ML
Source: Wikipedia
Google is most acquisitive (21 companies) in the space followed by Facebook (10 companies)
8. AI / ML Venture Funding Analysis: Methodology
• Created a database of over 2800
AI/ML companies from several sources
including Angel list, Crunch base,
Tracxn, Venture scanner, Portfolios of
major VCs, News Reports & Secondary
Research
• Weeded out public, acquired, closed
down and non existent companies
(with no website) arriving at a list of
1781 companies
• Filtered the list further to 312
companies based on funding > $100k
• In addition to the focus areas in AI /
ML areas defined on slide 3, we have
extended our analysis to areas like
augmented reality, image / facial
recognition, and drones that overlap
multiple areas.
2800
AI & ML companies from
sources: Angel List, Crunch
base, Tracxn, Venture
scanner, VC websites,
News articles & secondary
research
1781
Active companies after
weeding out public,
acquired, closed down,
non existent companies
312
Companies that
have external
funding of >$100k
9. Active AI / ML Ventures by Country in 2015
More than half of the AI/ML companies are based in the US
929
127 108
77
52 44 34 32 29 19
330
0
100
200
300
400
500
600
700
800
900
1000
USA UK India Canada Germany France Israel Russia China Netherlands Others
n= 1781
10. AI / ML Ventures based on Funding and Location
SF Bay Area has the highest density of funded startups followed by New York & London
Out of funded companies , nearly 40% are in the SF Bay Area &
70% in North America
Nearly 18% of companies are funded
68
49
26
12 12
8
0
10
20
30
40
50
60
70
80
Silicon
Valley
San
Francisco
NewYork London Seattle Berlin
312
1469
Funded
Companies
n=312
11. AI / ML Startups are still in their Infancy
62% of the startups still pre series A
193
72
26
10
5 1 5
0
50
100
150
200
250
Seed/Angel Series A Series B Series C Series D Series E Other
n=312
12. Venture Funding and Most Active VCs in AI / ML
Khosla Ventures:
Blue River, Scaled Inference, Atomwise, Lumiata,
Kaggle, Idibon, Metamind, Pymetrics, Ayasdi, Catalia
Health, Theatro, Thync
Google Ventures:
Expect Labs, Wonder Workshop, Clarifai, Orbital
Insights, Airware, Agent, AltspaceVR, Bento, Building
Robotics, Framed, Skycatch
Intel Capital:
API.ai, Cloudmade, Emotient, Expect Labs, Eyesmart,
PrecisionHawk, Hooklogic, Prelert, Reflektion, Total
Immersion, Fortscale,Whoknows, Incoming Media,
Occipital
Two Sigma Ventures:
Anki, 3D Robotics, Rethink Robotics, Jibo, Kasisto,
Dextro, Socure, Floored, Canary, Zymergen, Indico
Data,
RRE Ventures:
DigitalGenius, Yhat, Clearpath Robotics, Jibo, Palantir,
Giphy, Viglink, Airware0
50
100
150
200
250
300
350
2010 2011 2012 2013 2014
14
12 12 12
8
0
2
4
6
8
10
12
14
16
Intel Capital Khosla
Ventures
Two Sigma
Ventures
Google
Ventures
RRE
Ventures
Source: Company Websites
Source: CB Insights
No. of Investments in AI/ML companies
Venture Investments in $M in AI/ML companies
300% increase in venture funding from ‘13 to ‘14. Intel Capital, Google, Two sigma & Khosla
ventures most active in investing in AI / ML
13. Funded Ventures in various fields of AI / ML
Machine learning, Robotics, AR and Image recognition are most actively funded areas
n=31292
58
36 34 33
26
11 10 8
4
0
10
20
30
40
50
60
70
80
90
100
ML
(excluding
Deep
learning and
predictive
analytics)
Robotics &
Drones
AI
(excluding
NLP, ML,
Robotics,
Computer
Vision)
Augmented
Reality
Image &
Face
Recognition
NLP Predictive
Analytics
(clustering,
SVM,
Bayesian
networks)
Computer
Vision
Deep
Learning &
Neural
Networks
Others
14. Major Fields for AI / ML Venture Investment by Geography
North America is leading the way but Europe has significant presence in AI & AR areas
n=312
68
44
22
20 20 19
11
6 6
2
17
10 9
14
6
13
0
2 2 2
7
4
2 2 2
0
2
0
0
10
20
30
40
50
60
70
80
ML
(excluding
Deep
learning
and
predictive
analytics)
Robotics &
Drones
AI
(excluding
NLP, ML,
Robotics,
Computer
Vision)
Augmented
Reality
Image &
Face
Recognition
NLP Predictive
Analytics
(clustering,
SVM,
Bayesian
networks)
Computer
Vision
Deep
Learning &
Neural
Networks
Others
North America
Europe
Asia/Other
15. Areas of Application of Venture funded companies in AI/ML
72% of the funded startups targeting enterprise applications
n=312
(consumer apps, consumer electronics,
educational applications for consumers
& toys)
224
88
0
50
100
150
200
250
Enterprise Consumer
16. AI / ML Ventures with Applications across Industries
Impact across a wide range of industries
50
38
30
23 23 23
16
14 14
9 8 7 6 6 5 5
35
0
10
20
30
40
50
60
ConsumerApps
IndustrialAutomation
AI/MLasaService
Healthcare
Media
Marketing
Advertising
Security
FinancialServices
Ecommerce
HR
Agriculture
Education
Enterpriseproductivity
ITServices
CustomerService
Others
n=312
17. Aerospace
Cumbersome & manual process
of maintenance and repair using
field manuals that have to be
frequently updated
Field service agents can call or chat with
support from his/her augmented reality view
Today Future
Companies making it happen: Atheer Labs, Augmate, Infinity AR, Total Immersion,
Vuzix
Pic Courtesy: Atheer Labs
18. Agriculture
Farming decisions based on tradition and
intuition
Machine learning algorithms using sensor data
and aerial imaging help farmers make
intelligent data based decisions increasing
yield
Today Future
Companies making it happen: Blue River, Farmlogs, Greensight, Mavrx, Pulsepod,
Terravion
Pic Courtesy: Farmlogs
19. Automotive
Cars driven by humans, prone to errors
(nearly 1.3M people die in road accidents
every year)
Driverless cars – leading to comfortable
experience & less human fatalities
Today Future
Companies making it happen: BMW, Daimler Benz, Google
Pic Courtesy: Google
20. Background Checks
Checking of background information,
documents and identity manually taking 1-2
weeks
Automated background checking process
through APIs, real time ID authentication using
image recognition. Nearly 60% reduction in
costs
Today Future
Companies making it happen: Onfido
Pic Courtesy: Onfido
21. Communications
People can talk to one another only in a
common language that they speak
People will be able to talk to one another
without knowing the other person’s language
– Nothing lost in translation
Today Future
Companies making it happen: Lexifone
Pic Courtesy: Clker.com
Hi, How are
you
I’m fine thank
you
Hi, How are
you
मैं ठीक हूं
धन्यवाद
22. Customer Care
Time consuming process of
Authentication
Biometric Voice recognition based instant
authentication
Today Future
Companies making it happen: Agnitio, Nuance, Verbio, Voicebase, Voiceitt, VoiceVault
Sir, Please help me with
the authentication & tell
me your DOB, Address,
Mobile No.
My Password is XXXXX
23. Customer Care
Cumbersome & time wasting
Voice Menu
Virtual assistant that can converse like humans
& assist without Menus
Today Future
Companies making it happen: DigitalGenius, Expect Labs, Nuance
Press 1 for Credit
Cards, Press 2 for
Debit Cards, Press 3
for Loans, Press 4 for
Netbanking……
24. Healthcare
Doctor reads static patient charts
before or after visiting a patient
Doctor can read all relevant reports
dynamically using gestures during her patient
visit
Today Future
Companies making it happen: Atheer Labs, Augmedix, Infinity AR
25. Media
Watching ads on TV is avoided as they are
not actionable and mostly irrelevant
Automatic content recognition will allow
advertisers/ programmers to inject
interactivity & context relevant content
Today Future
Companies making it happen: Cognitive Networks, Datascription, Dextro, Enswers, Magic
Pony Technology, Persado, Videntifier Technologies
Wonder if
that Jersey
came in my
size
Just ordered
the Jersey
directly
Pic Courtesy: Forbes
26. Navigation
Driver needs to divert his gaze or
has to give rigid voice instructions
On windshield navigation with heads up
display that recognizes the surrounding and
gives instructions
Today Future
Companies making it happen: Nuviz, Wayray
Pic Courtesy: Wayray
27. Office Productivity
Mundane tasks in office leading to decreased
productivity
Automatic meeting schedulers, note takers,
speech to text transcription & virtual personal
assistants will improve productivity
Today Future
Companies making it happen: Assistant.to, Gridspace, Idibon, Robin Labs, Thoughtly,
X.ai, Zahdoo
Pic Courtesy: Typepad & Coolcontourproducts.com
28. Oil and Gas
Crack Detection: It takes human 5
hours per inspection with 92%
accuracy (Avg cost ~ $7.5)
20 seconds with 94% accuracy through image
recognition (Average Cost ~ $2)
Today Future
Companies making it happen: Tractable
Pic Courtesy: Wikipedia
29. Recruiting
Impossible to manage candidates with
required behavioral skills
Neuroscience based games will match
candidates with required skills
Today Future
Companies making it happen: Connectifier, Pymetrics, Talentoday
Pic Courtesy: Pymetrics
30. Wealth Management
Stock trading & investing happens mainly on
personal skills and divine luck
Sentiment analysis, crowd sourced research &
algorithms will make investing more
transparent and better informed
Today Future
Companies making it happen: Betterment, Estimize, Narrative Science, Personal Capital,
Sigfig, Wealthfront