Eyebrows were raised after Paris-based AI startup Mistral raised €105m with no product, a mere four weeks after launching. While some welcomed the raise as a milestone for European tech, others saw it as sign of AI hype reaching a feverish peak.
Their pitch memo focuses on two main selling points:1) that Europe has “yet to see the appearance of a serious contender” in building foundational models, and that Mistral will play a big role in this “major geopolitical issue”, and 2) embracing an open-source approach (unlike OpenAI's “black box” system) will make it easier for companies to build “better, faster” products. The company raised from notable investors including Lightspeed Ventures, French billionaire Xavier Niel and former Google CEO Eric Schmidt.
See more: bestpitchdeck.com/mistral
GTX's $25M pitch deck: new crypto exchange by 3AC & CoinFLEX foundersPitch Decks
The founders of the now-defunct crypto hedge fund, Three Arrows Capital (3AC) and co-founders of CoinFLEX (which filed for restructuring last year) are teaming up to raise $25 million to establish a new crypto exchange called GTX.
The launch of this new exchange comes two months after the infamous collapse of leading crypto exchange FTX, which left over a million creditors without compensation. The name of the exchange, GTX, is even a play on FTX, with one pitch deck opening with the line “because G comes after F.”
Regardless of the surrounding controversy, the GTX pitch deck offers unique insight into how repeat founders can bounce back from a failed startup and raise funding from investors for new ventures:
Read more: vip.graphics/gtx-pitch-deck
See details: bestpitchdeck.com/gtx
Scipher Medicine's $110M pitch deck for precision medicinePitch Decks
Scipher Medicine use a patient's unique molecular data to deliver optimal therapy, seeking to improve lives and save money through precision medicine.
Their platform is intended to employ artificial intelligence to decide which drug will be most effective for each patient. Schiper is constructing a molecular map of all protein interactions to identify genomic signatures and link those to disease and predictive treatment outcomes. Scipher Medicine can predict whether a patient will respond to a targeted medicine using a simple blood sample and RNA analysis before the therapy is prescribed.
Having raised a total of $117 million in three financing rounds since its inception in 2015, Scipher Medicine announced the close of a $110M round led by Cowen Inc., with participation from new investors Neuberger Berman, Hitachi Ventures, Laurion Capital Management LP, and Monashee Investment Management LLC. Existing investors Northpond Ventures, aMoon Fund, Khosla Ventures, Optum Ventures, Echo Health Ventures, and Alumni Ventures also participated.
Here is the 24-slide pitch deck Scipher Medicine used to secure $110 million from leading growth & venture capital firms:
Read more: vip.graphics/scipher-pitch-deck/
See the deck: bestpitchdeck.com/scipher
"Founded in 2012, Ageras is a FinTech startup that connects small and medium-sized businesses with professional service providers such as accountants, bookkeepers, and lawyers. The startup’s core product is an online marketplace that matches customers with the best service providers for their needs and budget.
The Copenhagen-based startup has expanded to six markets across Europe and the US, serving over 300,000 customers and 6,000 service providers. The company also offers complementary products such as Billy, a cloud-based accounting software, and Meneto, a digital tax assistant.
Ageras used this pitch deck to raise $35 million in a private equity round led by Lugard Road Capital, with participation from existing investors Investcorp and Rabo Frontier Ventures. The funding will be used to further grow its product portfolio and enter new markets."
GTX's $25M pitch deck: new crypto exchange by 3AC & CoinFLEX foundersPitch Decks
The founders of the now-defunct crypto hedge fund, Three Arrows Capital (3AC) and co-founders of CoinFLEX (which filed for restructuring last year) are teaming up to raise $25 million to establish a new crypto exchange called GTX.
The launch of this new exchange comes two months after the infamous collapse of leading crypto exchange FTX, which left over a million creditors without compensation. The name of the exchange, GTX, is even a play on FTX, with one pitch deck opening with the line “because G comes after F.”
Regardless of the surrounding controversy, the GTX pitch deck offers unique insight into how repeat founders can bounce back from a failed startup and raise funding from investors for new ventures:
Read more: vip.graphics/gtx-pitch-deck
See details: bestpitchdeck.com/gtx
Scipher Medicine's $110M pitch deck for precision medicinePitch Decks
Scipher Medicine use a patient's unique molecular data to deliver optimal therapy, seeking to improve lives and save money through precision medicine.
Their platform is intended to employ artificial intelligence to decide which drug will be most effective for each patient. Schiper is constructing a molecular map of all protein interactions to identify genomic signatures and link those to disease and predictive treatment outcomes. Scipher Medicine can predict whether a patient will respond to a targeted medicine using a simple blood sample and RNA analysis before the therapy is prescribed.
Having raised a total of $117 million in three financing rounds since its inception in 2015, Scipher Medicine announced the close of a $110M round led by Cowen Inc., with participation from new investors Neuberger Berman, Hitachi Ventures, Laurion Capital Management LP, and Monashee Investment Management LLC. Existing investors Northpond Ventures, aMoon Fund, Khosla Ventures, Optum Ventures, Echo Health Ventures, and Alumni Ventures also participated.
Here is the 24-slide pitch deck Scipher Medicine used to secure $110 million from leading growth & venture capital firms:
Read more: vip.graphics/scipher-pitch-deck/
See the deck: bestpitchdeck.com/scipher
"Founded in 2012, Ageras is a FinTech startup that connects small and medium-sized businesses with professional service providers such as accountants, bookkeepers, and lawyers. The startup’s core product is an online marketplace that matches customers with the best service providers for their needs and budget.
The Copenhagen-based startup has expanded to six markets across Europe and the US, serving over 300,000 customers and 6,000 service providers. The company also offers complementary products such as Billy, a cloud-based accounting software, and Meneto, a digital tax assistant.
Ageras used this pitch deck to raise $35 million in a private equity round led by Lugard Road Capital, with participation from existing investors Investcorp and Rabo Frontier Ventures. The funding will be used to further grow its product portfolio and enter new markets."
Rokoko was founded by Jakob Balslev, Matias Søndergaard, and Anders Klok in March 2014. Initially, they launched a Kickstarter campaign for the Smartsuit Pro.
The mocap (motion capture) company has more than 50,000 users all over the world, ranging from indie creators to some of the biggest names in the business.
Rokoko used this pitch deck to raise a $3M strategic round which was specifically pulled together to bring the creators of Zepeto onto Rokoko’s cap table. The funding round values Rokoko at over $80 million, led by Naver Z.
Five Flute is an issues management app that helps engineers develop better products with less effort. You can think of it like Github issues for hardware teams. We help teams of mechanical and electrical engineers reduce the coordination and communication effort during development by giving them one place for tracking and managing design and development issues, and then keeping these issues connected to the parts, assemblies and physical hardware they impact. Teams that use Five Flute keep move faster with fewer mistakes and keep everyone on the same page regarding engineering decisions. Use it for requirements management, design reviews, test planning, bug tracking, and as a hardware specific to-do list. It's super flexible.
Bolt pitch deck: $393M Series D, $6B+ valuationPitch Decks
One-click checkout Bolt used this 12-page deck to describe raise $393M in Series D funding for expanding its network of 5.6 million consumers.
Bolt is an innovative payment processing company that offers an integrated checkout experience that enables retailers to convert and retain more consumers. This round of $333 million in Series D funding and $60 million in follow-on capital will “fuel commerce’s first federated checkout network”, and brings Bolt’s total funding to over $600 million.
Most impressively, the round comes at ~18× the valuation that Bolt was priced at just eighteen months prior, using the simple 12-slide deck below:
See more at https://vip.graphics/bolt-pitch-deck-series-d/
Ark Kapital is a data-driven precision financing company that helps early-stage startups thrive by providing long-term loans while keeping founders in control and lowering the risk for investors.
The Swedish-based startup, which was launched in 2021, analyses the financial health of early-stage tech businesses using AI and machine learning and provides precise loans based on their performance.
Ark Kapital announced that it has raised $182 million in a mix of debt and equity funding. The round was led by Local Globe, with participation from Creandum and angel investors including Supercell CEO Ilkka Paananen, iZettle founder Jacob de Geer, and EQT Ventures founding partner Hjalmar Winbladh.
Read more: vip.graphics/ark-pitch-deck/
See the deck: bestpitchdeck.com/ark
Paddle is a revenue delivery platform, which allows B2B SaaS businesses to amalgamate their workflow and become more efficient at selling digital products and subscriptions. The UK-based company is on a mission to take away the pain of payments fragmentation in a unique way, by serving as the merchant of record for software & SaaS companies.
Used by over 2,000 software sellers in 245 countries and territories globally, Paddle raised a £52 million ($68 million) Series C in 2021 from investors including FTV Capital, Kindred Capital, Notion Capital, and 83North.
See more: bestpitchdeck.com/paddle-series-c
Kryptomon pitch deck: $10M Series A for NFT-based P2E gamingPitch Decks
Kryptomon is a blockchain-based NFT Play-and-Earn game where Pokémon meets Tamagotchi and CryptoKitties. In this metaverse game, community members play as 'Trainers' of individual monsters.
Founded in April 2021 by Umberto Canessa, the crypto game has demonstrated tremendous growth: bragging over 500,000 social followers and $13 million in NFT transactions in less than 5 months.
Within less than a year of launch, the company raised $10 million in a Series A round led by NFX, with additional backing by PLAYSTUDIOS ($MYPS), Griffin Gaming Partners, Tal Ventures, and Vikram Pandit, former CEO of Citigroup.
Read more: vip.graphics/kryptomon-pitch-deck
See more: bestpitchdeck.com/kryptomon
Yuga Labs, the company that created the wildly popular Bored Ape Yacht Club NFT collection, is hoping to make hundreds of millions of dollars by selling off virtual plots of land. According to a leaked pitch deck obtained by The Block, the company also plans to launch a sweeping new metaverse initiative, as well as its own token.
Yuga's revenue last year reached a whopping $127 million, a figure it anticipates will reach $455 million by 2022 — largely from the sale of virtual land.
This leak comes after a flurry of activity in the blue-chip corner of the NFT sector: most notably, Yuga Labs announced the acquisition of the CryptoPunks and Meebits NFT projects’ intellectual property from Larva Labs just days prior. As of today, Yuga Labs owns two of the most valuable NFT projects on the market: BAYC and CryptoPunks projects have a combined trading volume of more than US$3 billion.
Read more: vip.graphics/yuga-labs-pitch-deck/
See the deck: bestpitchdeck.com/yuga-labs
Supliful's $1.1M pitch deck for white-label influencer supplementsPitch Decks
On-demand supplement fulfilling and dropshipping solution Supliful allows anyone to launch their own custom-designed supplement product line.
The company's platform lets nutrition experts, fitness coaches, biohackers and solopreneurs create their own online supplement brand without upfront investments. Supliful was founded in 2020 by Mārtiņš Lasmanis, Rihards Piks, and Rudolfs Janitis. Supliful claims it raised $1.1M in pre-seed funding with this 22-slide deck.
OurSong pitch deck: $7.5M for John Legend's music NFT platformPitch Decks
OurSong began as a research project at the Ideation Lab of Taiwan's leading media technology company, KKBOX Group. The company was launched by 12-time Grammy winner John Legend and a team of five co-founders seeking to build a better system for creators to be discovered, monetize their work, and engage with fans through NFTs.
Their mobile app aims to build a community for digital art creators and artists by leveraging NFTs to help them gain fans and earn from their creative works.
In April 2022, the company announced it raised $7.5 million in seed funding led by Infinity Ventures and Animoca Brand.
Read more: https://vip.graphics/oursong-pitch-deck
See the deck: https://bestpitchdeck.com/oursong
Company Presentation by Peter Bakenecker, Division President Germany & Switzerland at Mastercard at the Axel Springer NOAH Conference 2018 in Berlin, Tempodrom 6-7 June 2018.
leewayhertz.com-How to build a generative AI solution From prototyping to pro...KristiLBurns
Generative AI has gained significant attention in the tech industry, with investors, policymakers, and the society at large talking about innovative AI models like ChatGPT and Stable Diffusion.Generative AI has gained significant attention in the tech industry, with investors, policymakers, and the society at large talking about innovative AI models like ChatGPT and Stable Diffusion.
Generative AI: A Comprehensive Tech Stack BreakdownBenjaminlapid1
Build a reliable and effective generative AI system with the right generative AI tech stack that helps create smarter solutions and drive growth.
Click here for more information: https://www.leewayhertz.com/generative-ai-tech-stack/
Rokoko was founded by Jakob Balslev, Matias Søndergaard, and Anders Klok in March 2014. Initially, they launched a Kickstarter campaign for the Smartsuit Pro.
The mocap (motion capture) company has more than 50,000 users all over the world, ranging from indie creators to some of the biggest names in the business.
Rokoko used this pitch deck to raise a $3M strategic round which was specifically pulled together to bring the creators of Zepeto onto Rokoko’s cap table. The funding round values Rokoko at over $80 million, led by Naver Z.
Five Flute is an issues management app that helps engineers develop better products with less effort. You can think of it like Github issues for hardware teams. We help teams of mechanical and electrical engineers reduce the coordination and communication effort during development by giving them one place for tracking and managing design and development issues, and then keeping these issues connected to the parts, assemblies and physical hardware they impact. Teams that use Five Flute keep move faster with fewer mistakes and keep everyone on the same page regarding engineering decisions. Use it for requirements management, design reviews, test planning, bug tracking, and as a hardware specific to-do list. It's super flexible.
Bolt pitch deck: $393M Series D, $6B+ valuationPitch Decks
One-click checkout Bolt used this 12-page deck to describe raise $393M in Series D funding for expanding its network of 5.6 million consumers.
Bolt is an innovative payment processing company that offers an integrated checkout experience that enables retailers to convert and retain more consumers. This round of $333 million in Series D funding and $60 million in follow-on capital will “fuel commerce’s first federated checkout network”, and brings Bolt’s total funding to over $600 million.
Most impressively, the round comes at ~18× the valuation that Bolt was priced at just eighteen months prior, using the simple 12-slide deck below:
See more at https://vip.graphics/bolt-pitch-deck-series-d/
Ark Kapital is a data-driven precision financing company that helps early-stage startups thrive by providing long-term loans while keeping founders in control and lowering the risk for investors.
The Swedish-based startup, which was launched in 2021, analyses the financial health of early-stage tech businesses using AI and machine learning and provides precise loans based on their performance.
Ark Kapital announced that it has raised $182 million in a mix of debt and equity funding. The round was led by Local Globe, with participation from Creandum and angel investors including Supercell CEO Ilkka Paananen, iZettle founder Jacob de Geer, and EQT Ventures founding partner Hjalmar Winbladh.
Read more: vip.graphics/ark-pitch-deck/
See the deck: bestpitchdeck.com/ark
Paddle is a revenue delivery platform, which allows B2B SaaS businesses to amalgamate their workflow and become more efficient at selling digital products and subscriptions. The UK-based company is on a mission to take away the pain of payments fragmentation in a unique way, by serving as the merchant of record for software & SaaS companies.
Used by over 2,000 software sellers in 245 countries and territories globally, Paddle raised a £52 million ($68 million) Series C in 2021 from investors including FTV Capital, Kindred Capital, Notion Capital, and 83North.
See more: bestpitchdeck.com/paddle-series-c
Kryptomon pitch deck: $10M Series A for NFT-based P2E gamingPitch Decks
Kryptomon is a blockchain-based NFT Play-and-Earn game where Pokémon meets Tamagotchi and CryptoKitties. In this metaverse game, community members play as 'Trainers' of individual monsters.
Founded in April 2021 by Umberto Canessa, the crypto game has demonstrated tremendous growth: bragging over 500,000 social followers and $13 million in NFT transactions in less than 5 months.
Within less than a year of launch, the company raised $10 million in a Series A round led by NFX, with additional backing by PLAYSTUDIOS ($MYPS), Griffin Gaming Partners, Tal Ventures, and Vikram Pandit, former CEO of Citigroup.
Read more: vip.graphics/kryptomon-pitch-deck
See more: bestpitchdeck.com/kryptomon
Yuga Labs, the company that created the wildly popular Bored Ape Yacht Club NFT collection, is hoping to make hundreds of millions of dollars by selling off virtual plots of land. According to a leaked pitch deck obtained by The Block, the company also plans to launch a sweeping new metaverse initiative, as well as its own token.
Yuga's revenue last year reached a whopping $127 million, a figure it anticipates will reach $455 million by 2022 — largely from the sale of virtual land.
This leak comes after a flurry of activity in the blue-chip corner of the NFT sector: most notably, Yuga Labs announced the acquisition of the CryptoPunks and Meebits NFT projects’ intellectual property from Larva Labs just days prior. As of today, Yuga Labs owns two of the most valuable NFT projects on the market: BAYC and CryptoPunks projects have a combined trading volume of more than US$3 billion.
Read more: vip.graphics/yuga-labs-pitch-deck/
See the deck: bestpitchdeck.com/yuga-labs
Supliful's $1.1M pitch deck for white-label influencer supplementsPitch Decks
On-demand supplement fulfilling and dropshipping solution Supliful allows anyone to launch their own custom-designed supplement product line.
The company's platform lets nutrition experts, fitness coaches, biohackers and solopreneurs create their own online supplement brand without upfront investments. Supliful was founded in 2020 by Mārtiņš Lasmanis, Rihards Piks, and Rudolfs Janitis. Supliful claims it raised $1.1M in pre-seed funding with this 22-slide deck.
OurSong pitch deck: $7.5M for John Legend's music NFT platformPitch Decks
OurSong began as a research project at the Ideation Lab of Taiwan's leading media technology company, KKBOX Group. The company was launched by 12-time Grammy winner John Legend and a team of five co-founders seeking to build a better system for creators to be discovered, monetize their work, and engage with fans through NFTs.
Their mobile app aims to build a community for digital art creators and artists by leveraging NFTs to help them gain fans and earn from their creative works.
In April 2022, the company announced it raised $7.5 million in seed funding led by Infinity Ventures and Animoca Brand.
Read more: https://vip.graphics/oursong-pitch-deck
See the deck: https://bestpitchdeck.com/oursong
Company Presentation by Peter Bakenecker, Division President Germany & Switzerland at Mastercard at the Axel Springer NOAH Conference 2018 in Berlin, Tempodrom 6-7 June 2018.
leewayhertz.com-How to build a generative AI solution From prototyping to pro...KristiLBurns
Generative AI has gained significant attention in the tech industry, with investors, policymakers, and the society at large talking about innovative AI models like ChatGPT and Stable Diffusion.Generative AI has gained significant attention in the tech industry, with investors, policymakers, and the society at large talking about innovative AI models like ChatGPT and Stable Diffusion.
Generative AI: A Comprehensive Tech Stack BreakdownBenjaminlapid1
Build a reliable and effective generative AI system with the right generative AI tech stack that helps create smarter solutions and drive growth.
Click here for more information: https://www.leewayhertz.com/generative-ai-tech-stack/
This is an article about Generative AI. It discusses what it is and the different techniques used to create it. It also goes into the potential uses of Generative AI. Some of the important points from this article are that Generative AI is still in its early stages but has already shown promising results. It is also important to note that Generative AI can be used to create fake data that is indistinguishable from real data.
https://www.ltimindtree.com/wp-content/uploads/2023/01/DeepPoV-Generative-AI.pdf
Generative AI models are transforming various fields by creating realistic images, text, music, and videos. This guide will take you through the essential steps and considerations for building a generative AI model, providing a comprehensive understanding of the process.
Building a generative AI solution involves defining the problem, collecting and processing data, selecting suitable models, training and fine-tuning them, and deploying the system effectively. It’s essential to gather high-quality data, choose appropriate algorithms, ensure security, and stay updated with advancements.
Investigate briefly 5 companies that are leveraging GPT3. For each company provide details addressing the following topics
indicate the problem that the company is addressing and why is the problem important
what are other ways to solve this problem and is anyone doing it (competition)
test out the product (free version) and provide your comments on one slide
how does the company expect to make money
Would you invest in this company (hypothetically if you had money and had to invest) - give reasons for your answer
Each company description to be in approximately 250 words - so 1250 words for 5 companies approx.
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Produced by Nathan Benaich and Air Street Capital team
State of AI Report 2023 - ONLINE presentationssuser2750ef
State of AI Report 2023 - ONLINE.pptx
When conducting a PEST analysis for the Syrian conflict, it's important to consider the political, economic, socio-cultural, and technological factors that have influenced and continue to impact the situation in Syria. Here's a high-level overview of a PEST analysis for the Syrian conflict:
1. Political Factors:
- Government Instability: Ongoing civil war and conflict have led to political instability and a complex power struggle between various factions and international players.
- Foreign Intervention: Involvement of external powers and regional actors has exacerbated the conflict and added geopolitical complexities to the situation.
- International Relations: Relations with global powers like the United States, Russia, and regional players like Iran and Turkey significantly impact the conflict dynamics.
2. Economic Factors:
- Humanitarian Crisis: The conflict has resulted in a severe humanitarian crisis, causing widespread displacement, destruction of infrastructure, and economic decline.
- Sanctions and Trade Barriers: International sanctions and disrupted trade have further worsened the economic situation in Syria, affecting the livelihoods of the population.
- Resource Depletion: Conflict-driven resource depletion, including loss of agricultural lands and disruption of industries, has weakened the economy.
3. Socio-cultural Factors:
- Civilian Suffering: The conflict has led to a significant loss of life, displacement of populations, and severe trauma among civilians, impacting social cohesion and community structures.
- Ethnic and Religious Divisions: Deep-seated ethnic and religious divisions have fueled the conflict, leading to sectarian tensions and societal fragmentation.
- Refugee Crisis: The conflict has triggered a massive refugee crisis, with millions of Syrians seeking asylum in neighboring countries and beyond, straining regional stability.
4. Technological Factors:
- Communication and Propaganda: Technology, including social media, has been used for communication, mobilization, and spreading propaganda by various actors in the conflict.
- Warfare Technology: Advancements in warfare technology and the use of drones, cyber warfare, and other advanced weaponry have transformed the nature of conflict in Syria.
- Cybersecurity Concerns: The conflict has also raised concerns about cybersecurity threats, misinformation campaigns, and digital vulnerabilities in the region.
This analysis provides a broad understanding of the multifaceted nature of the Syrian conflict, highlighting the diverse factors at play and the complex challenges facing Syria and the international community.
AI and ML Series - Introduction to Generative AI and LLMs - Session 1DianaGray10
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
How Decentralized AI can Dominate the Global AI EcosystemEficode
Ben Goertzel
CEO – SingularityNET, Chief Scientist – Hanson Robotics, the creator of the robot Sophia.
Dr. Goertzel is one of the world’s foremost experts in Artificial General Intelligence, a subfield of AI oriented toward creating thinking machines with general cognitive capability at the human level and beyond.
With the evolution of no-code AI, sectors such as web development are advancing while others are just emerging. Now, with these no-code AI platforms, businesses have a chance to explore the technology without needing to hire tech experts or adopting expensive strategies.
NO-CODE PLATFORMS HAVE MADE IT EASY TO CREATE PROGRAMS THAT USE ADVANCED TECHNOLOGIES. THE INTRODUCTION OF THESE PLATFORMS HAS RESULTED IN AN INCREASING NUMBER OF BUSINESSES ATTEMPTING TO USE THEIR CAPACITY TO BUILD AI SOLUTIONS.
With this, visual drag-and-drop tools come into the picture, aiding data scientists in filling the void and making AI less daunting for people with non-technical backgrounds.
This article discusses the top no-code platforms for building AI solutions.
MonkeyLearn
MonkeyLearn is an all-in-one text analysis and data visualization studio that can be used to extract topic, sentiment, intent, keywords, and other information from unstructured text-based data. Automatically tagging business data, presenting actionable insights and trends, and simplifying text classification and extraction processes are just a few of the features. It integrates with Zendesk, RapidMinder, and Google products, with a few others on the way. Also, it is one of the best blog resources for text analysis.
RunwayML
RunwayML is a tool for creators that focuses on creative work that involves dealing with pictures, videos, text, latent spaces, and segmentation masks, as well as motion capture, backdrop removal, and style transfer. They have a Generative Engine, which is a storytelling machine that generates visuals automatically as you write.
Finally
Businesses are increasingly turning to no-code platforms for a variety of reasons. Access to developers and software engineers slows project delivery, partly owing to the ripple impact on workforce management, and this is where technology can help. The unicorn we all want to catch is not only enabling your team to create solutions but also being relevant and competitive in the present context.
For more such updates and perspectives around Digital Innovation, IoT, Data
Infrastructure, AI & Cybersecurity, go to AI-Techpark.com.
Explore the transformative power of generative AI in our latest E42 Blog post, diving deep into its capabilities for enterprise-level process automation. From explaining the core principles of generative AI, to uncovering insights into the crucial role played by on-premises Large Language Models (LLMs) in facilitating secure and compliant digital transformations across industry verticals—the article also provides a glimpse into the future of AI, where multimodal enhancements and breakthroughs in bias mitigation promise to reshape the landscape of process automation.
AI & ML: Although it has been around for a long time, artificial intelligence was once thought to be incredibly challenging. It was typical for scientists and developers to avoid examining utilising it.
To know more about, Top AI & ML tools and frameworks, see https://www.logic-fruit.com/blog/al-ml/top-ai-ml-tools-and-frameworks/
About Logic Fruit Technologies
Logic Fruit Technologies is a product engineering R&D & consulting services provider for embedded systems and application development. We provide end-to-end solutions from the conception of the idea and design to the finished product. We have been servicing customers globally for over a decade.
The company has specific experience in various fields, such as
FPGA Design & hardware design
RTL IP Design
A variety of digital protocols
Communication buses as1G, 10G Ethernet
PCIe
DIGRF
STM16/64
HDMI.
Logic Fruit Technologies is also an expert in developing,
software-defined radio (SDR) IPs
Encryption
Signal generation
Data analysis, and
Multiple Image Processing Techniques.
Recently Logic Fruit technologies are also exploring FPGA acceleration on data centers for real-time data processing.
**Our Social Media Channels**
Facebook: https://www.facebook.com/LogicFruit/
Twitter: https://twitter.com/logicfruit
LinkedIn: https://www.linkedin.com/company/logi…
Website: https://www.logic-fruit.com/
#LFT #LogicFruitTechnologies #LogicFruit
Interested to view more SlideShares, Click on the below links,
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https://www.slideshare.net/LogicFruit/arinc-629-digital-data-bus-specifications/LogicFruit/arinc-629-digital-data-bus-specifications
https://www.slideshare.net/LogicFruit/afdx
https://www.slideshare.net/LogicFruit/end-system-design-parameters-of-the-arinc-664-part-7
https://www.slideshare.net/LogicFruit/compute-express-link-cxl-everything-you-ought-to-know
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https://www.slideshare.net/LogicFruit/afdx-a-timedeterministic-application-of-arinc-664-part-7
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https://www.slideshare.net/LogicFruit/arinc-8182-standard-overview-and-its-characteristics
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How Mistral AI raised €105m with no pitch deck or product
1. mistral.ai strategic memo
Generative AI is a transformative technology
The last year has seen a spectacular acceleration in generative AI: systems able to generate
text / image conditioned on text and images. Those systems can help humans:
● produce superb creative content (text, code, graphics)
● read, process and summarise unstructured content streams thousands of times
faster than humans
● interact with the world (exposed through natural or application interfaces) to execute
workflows faster than ever before.
The power of generative AI was suddenly demonstrated to the general audience with the
release of ChatGPT; this kind of product has been in the making by only a few small teams
across the world — the few researchers of these teams are now the limiting factor to create
new economic actors in the field.
Generative AI is about to boost productivity in all sectors and create a new industry (10B
market size as of 2022, projected to be 110B by 2030, with an estimated growth rate of 35%
per year), by seamlessly enhancing the human mind with machine capabilities. It is a
transformative technology for the world economy that will change the nature of work to bring
positive societal changes.
An oligopoly is shaping up
Generative AI technologies are based on years of research made in many parts of the
industry and academia. The final breakthroughs, i.e. scaling training to internet-wide data
and aligning models with human feedback, finally made these technologies usable by many;
these breakthroughs were made by very few actors, the largest of which (OpenAI) appears
to have hegemonic intention over the market.
These very few actors train generative models and hold them as assets; they serve it to
thousands of third-party productivity enhancing products, in addition to also serving
first-party chatbot-like products. Dozens of third-party startups are created every month to
build various interfaces to these generative models.
We believe that most of the value in the emerging generative AI market will be located
in the hard-to-make technology, i.e. the generative models themselves. Those models
need to be trained on thousands of very powerful machines, on trillions of words coming
from high quality sources, which is one factor that sets a high barrier to entry. The second
1
2. important barrier lies in the difficulty to assemble an experienced team, something that
mistral.ai will be in a unique position of doing.
All major actors are currently US-based, and Europe has yet to see the appearance of a
serious contender. This is a major geopolitical issue given the strength (and dangers) of this
new technology. mistral.ai will become a European leader in productivity and creativity
enhancing AI, and guide the new industrial revolution that is coming.
Current generative AI do not meet market constraints
OpenAI and its current competitors have embraced a closed technology approach, which will
dramatically reduce their market reach. In that approach, the model is kept secret and is only
served through a text to text API endpoint. This raises the following important concerns for
businesses:
● Businesses wishing to use generative AI technology are forced to feed their
valuable business data and sensitive user data to a black-box model, typically
deployed in the public cloud. This creates safety issues: models kept secret cannot
be inspected to guarantee their outputs to be safe, thereby preventing them to be
deployed in safety-critical applications. It also raises legal problems, in particular the
one of falling under extraterritorial reach when sending personal data out of a
company's legal territory.
● Only exposing the output of models, instead of exposing the model entirely, makes it
harder to connect with other components (retrieval databases, structure inputs,
images and sounds). Hundreds of products are currently built by interconnecting
model outputs and inputs to create composed capacities (memory, vision, etc.).
Those products would work much better and faster were the models available
as white boxes (see for instance the Flamingo model, that combines white box
vision and text models into a text+vision model).
● The data used to train the model is kept secret, implying that we rely on a machine
that has unidentified sources, and can produce uncontrollable outputs. Filtering
efforts to address this issue are only a slim and breakable guarantee that the model
will not output sensitive content on which it may have been trained. As of April 2023,
this issue formed the basis of ChatGPT ban in Italy.
Disrupting the market from Europe
By creating mistral.ai, we intend to train state-of-the-art models with counter-positions to
closed-model current offerings. Our vision is to become a leading actor in the field, while
developing a very valuable business around integrating these models in the European
industry and beyond.
mistral.ai will become a research leader in the generative AI field, eventually offering
the best technology within 4 years. For this, we will first focus on several key
2
3. differentiators, and then expand to a full-scale R&D effort choosing the best solutions for
making new steps toward human-usable AI.
Specialising in the European market as a first step will create a defendable effort in itself —
technological counter-positioning will further contribute to our appeal. Many, if not most,
talents in the field of LLMs originate from Europe; as we have extensively tested, a large
number of them can be convinced to join forces in our project.
Technological counter-positioning
Our early differentiators, that constitute dead angles in our competitor’s strategy, are the
following:
● Take a more open approach to model development. We will release models with a
permissive open-source-software licence, that will be largely above the
competition in that category. We will distribute tools to leverage the power of these
white box models, and create a developer community around our trademark. This
approach is an ideological differentiator from OpenAI; it is a very strong point
argument for hiring highly coveted top researchers, and a strong accelerator
for development, as it will open the doors for many downstream applications from
motivated hackers. It will improve our reach for business development. We will
balance our open-source strategy with our economic interests, keeping the
strongest and most specialised models reserved for negotiated access.
○ We will dedicate 1% of our funding to a non-profit foundation in charge of
open-source community development.
● Whether open-source or licensed, the internals (architecture and trained weights) of
our models will always be accessible to our customers. This will allow tighter
integration with customer’s workflows, whose content can be fed into different
parts of the deep model, instead of serialising all content into input text, fed to
black box APIs.
● Increase the focus on data sources and data control. Our models will be trained
on high quality data content (in addition to scraped content) for which we will
negotiate licence agreements. This will allow us to train models much better than
currently available ones (e.g. Llama). Using deeply involved technology
(mixtures-of-experts and retrieval-augmented models), we will service models with
optional data sources access: for a paid premium, a certain model can be specialised
on finance/law/etc (this provides a substantial performance boost). With similar
technologies, our models will be able to provide on-the-fly differentiated data access
to employees with different views of the company intellectual property.
● Propose unmatched guarantees on security and privacy. Our models will be
deployable on private clouds and optionally directly on device, effectively making
privacy a non-concern by removing problematic flows. For this, we will direct our
R&D effort towards training small but super-efficient models, effectively proposing
models with the highest quality/cost ratio of the market. Our open-source strategy will
also be a guarantee of audibility when deploying our models in critical industries (in
particular the dual and the health sector).
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4. Business development
On the business side, we will provide the most valuable technology brick to the emerging
AI-as-a-service industry that will revolutionise business workflows with generative AI. We will
co-build integrated solutions with European integrators and industry clients, and get
extremely valuable feedback from this to become the main tool for all companies wanting to
leverage AI in Europe.
Integration with verticals can take different marketing forms, including licensing full access to
the models (including the trained weights), specialisation of models on demand, partnering
with integrators/consulting companies to establish commercial contracts for fully integrated
solutions. As detailed in our roadmap, we will explore and identify the best approach in
parallel to technological development.
What it takes to become a leader in AI
The rarest team
The founding team is composed of lead researchers in the field, formerly employed by
DeepMind and Meta, seasoned repeat French entrepreneurs and influential public leaders
● Arthur Mensch — CEO — Former staff research scientist at DeepMind
○ Lead author of several major contributions to LLM: Chinchilla, Retro, Flamingo
● Guillaume Lample — Chief scientist — Former senior staff research scientist at Meta
○ Lead Llama, major contribution of Meta to the field of large language models
● Timothée Lacroix — CTO — Former staff software engineer at Meta
○ Tech lead of Llama
● Jean-Charles Samuelian
○ CEO of Alan
● Charles Gorintin
○ CTO of Alan
● Cédric O
○ Former French Secretary of State for Digital Affairs
The first five employees that are already identified will be experienced researchers from
major tech companies. They are extremely motivated by the European and open-source
angle, and by the perspective of leaving companies that undergo constant reorganisations
due to the speed of development of generative AI.
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5. Infrastructure and data sources
Training a competitive model requires at least an exa-scale cluster for a few months. We
intend to rent such capacity for a full year, to allow the development of both open-source and
commercial models, with various capacities.
We have already negotiated competitive deals for renting computational power in Tier 1
cloud service providers (we are planning to reserve 1536 H100 starting in September, with a
summer ramp up). As mistral.ai has a strong European grounding, we will also be working
with both emerging European cloud providers as they grow their deep learning offers.
Having trained models at large-scale before has provided us know-hows that will allow us to
gain a factor 10-100 in training efficiency compared to public methods — our founders and
early employees know exactly what to do to train the strongest model for a given
computational budget.
Our early investors are also content providers in Europe, and will open all necessary doors
for acquiring high quality datasets on which our model can be trained and fine-tuned.
Access to major clients for usage exploration
The founding team is already organising business exploration with major French and
European industrial actors. A small product-oriented team (6 people at the end of first year)
will start developing leads while the technical team trains the valuable technological bricks.
The model team will remain 100% focused on the hard technological brick to avoid
distraction.
Business development will start in parallel to the first model family development, using the
following strategy
● Focus on exploring needs with a large industrial actors, accompanied by third-party
integrators that will be given full access to our best (non-open source) model
● Co-design of products with a few small emerging partners that focuses on
generative-AI products.
Exploration with businesses will be used to drive the design of the second generation of
models.
Roadmap
First year
We will train two generations of models, while developing business integration in parallel.
The first generation will be partially open-source and rely on technology well mastered by the
team. It will validate our competence near clients, investors and institutions. The second
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6. model generation will address the significant shortcomings of current models to become
safely and affordably usable by businesses.
Train the best open-source standard models
At the end of 2023, we will train a family of text-generating models that can beat ChatGPT
3.5 and Bard March 2023 by a large margin, as well as all open source solutions.
Part of this family will be open-sourced; we will engage the community to build on top of it
and make it the open standard.
We will service those models with the same endpoints as our competitor for a fee to acquire
third-party usage data, and create a few free consumer interfaces for trademark construction
and first-party usage data.
Customise for business needs and differentiate
In the following six months, these models will be accompanied by semantic embedding
models for content search, and multimodal plugins for handling visual inputs. Specialised
models, retrained on negotiated high quality data-sources will be prepared.
Business development will start in parallel to the first model family development: we intend to
have proof-of-concept integration by the end of Q1 2024.
On the technical side, during Q1-Q2 2024, we will focus on two major aspects that have
been under-estimated by incumbent companies:
● Train a model small enough to run on a 16GB laptop, while being a helpful AI
assistant
● Train models with hot-pluggable extra-context, ranging in the millions of extra
words, effectively merging language models and retriever systems.
In parallel, training and fine-tuning datasets will be constantly enriched through partnerships
and data acquisition.
At the end of Q2 2024, we intend to
● be distributing the best open-source text-generative model, with text and visual
output
● own generalist and specialist models with one the highest value/cost
● have scalable and usable and varied APIs for serving our models to third-party
integrators
● have privileged commercial relations with one or two major industrial actors
committed in using our technology
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7. Next stages
Competing and overcoming actors like OpenAI will require major investments in later stages
(GPT-4 cost a few hundred million dollars). Our purpose in the first year is to demonstrate
that we are one the best teams of the world in the AI race, able to ship models and model
affordances that rival the largest actors. Our experience as researchers in LLM will allow us
to be much more capital-efficient in the early stage than companies discovering the field or
pivoting towards it.
One of the North stars of mistral.ai will be safety: we will release models in a well-staged
way, making sure that our models can only be used for purposes aligned with our
values—for this, we’ll offer beta access to a “red team” to uncover inappropriate behaviours
and correct them.
We will thus convince major public and private institutions to trust us for constructing the
safe, controllable and efficient technology that we need to make humanity benefit from this
science breakthrough — effectively bringing institutions and states for the Serie A round. In
that round (Q3 2024), we expect to need to raise 200M, in order to train models exceeding
GPT-4 capacities.
Strong financing will allow us to train models on larger infrastructures, thereby establishing
us as a research leader in AI that will be the go-to provider of the European industry.
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