Lilu, Inc | 1,072 followers on LinkedIn. Lilu builds smart garments and wearables to empower new moms. We developed the first pumping bra with automated massage. | At Lilu we build tech-enabled products to empower new moms. We&#x27;re building a platform of smart products that leverage cutting edge ...

Lilu, Inc | LinkedIn

associated pain. Lilu’s customers ‘love this bra’ and call the device ‘awesome’ and a ‘breastfeeding savior’. ... New York, New York, United States. ... L&#x27;ATTITUDE Ventures. ... Seed round. ... Terms of Service | Privacy Policy | Sitemap | © 2024 Crunchbase Inc. All Rights Reserved.

Lilu - Crunchbase Company Profile & Funding

1 billion members | Manage your professional identity. Build and engage with your professional network. Access knowledge, insights and opportunities.

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Information on valuation, funding, cap tables, investors, and executives for Lilu. Use the PitchBook Platform to explore the full profile.

Lilu Company Profile: Valuation & Investors | PitchBook

Lilu is a women&#x27;s health company building tech-enabled products to make postpartum care more comfortable, efficient and pain-free.

Lilu, Inc | New York, NY, USA Startup

Lilu&#x27;s Garden is a Denver, CO based industrial hemp and CBD wholesaler with offices in Chicago, Denver and SoCal

Lilu's Garden LTD - Crunchbase Company Profile & Funding

FSA Store and HSA Store 5 POs, including an open PO for when we launch 2 new sizes (L and XL). Signed partnership with Mahmee end of 2020 so Lilu bra customers receive 24/7 text-based lactation support. Recently signed distrubtion agreements in Singapore and Spain to launch before End Of Q3 2021.

Lilu, Inc

Lilu bridges tradition &amp; technology. The Lilu Lactation Massager + Hands-Free Pumping Bra, allow breastfeeding moms to increase their milk supply, relieve engorgement, clogged ducts &amp; mastitis, gently and effectively. It mimics “Hands-on-Pumping”, without the need to use your hands.

Lilu | Lactation Massager + Hands-free pumping bra for nursing moms

Lilu, Inc is a Consumer Electronics, Wellness and Fitness Services, and Children company_reader located in New York, US with 20 employees. Find top employees, contact details and business statistics at RocketReach.

Lilu, Inc: Contact Details and Business Profile

It&#x27;s our business to grow yours! Own your market with leading B2B contact data combined with sales intelligence, engagement software, and workflow tools.

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Lilu. Additionally, ... University of Pennsylvania. ... Jun 16, 2021. ... There is no recent news or activity for this profile. ... Terms of Service | Privacy Policy | Sitemap | © 2024 Crunchbase Inc. All Rights Reserved.

Sujay Suresh Kumar - COO & Co-Founder @ Lilu - Crunchbase Person ...

If you’re stressed about pumping, sick of holding your pump on your own, and hoping to increase supply, I’d say give the Lilu a shot. ... Alex Hazlett is a Deputy Managing Editor at Mashable. Based out of Mashable&#x27;s New York HQ, she previously ran the company&#x27;s weekend coverage, oversaw ...

The Lilu Massage Bra lets you pump a little more milk a little ...

Lilu builds tech-enabled products using robotics and IoT to make post-partum care more comfortable, efficient and pain-free

With NFT sales having topped $2 billion during the first quarter of 2021, a raft of new platforms have come online seeking to capitalize on crypto’s latest gold rush. The appeal of a blockchain-based token that confers proof of ownership can be debated all day long, but to date the public’s appetite has been insatiable. NFTs representing digital merchandise, in-game collectibles, trading cards, artworks, audiovisual content and even albums have been minted, bought and sold at a frankly dizzying rate, and though talk of a “bubble” has been more or less ceaseless since the train left the station, investors continue to dream up ways of both exploiting the current mania and advancing the industry as a whole. Here are five new platforms hoping to become mainstays of the burgeoning NFT landscape. Nafter fuses NFTs and social media, helping influencers convert memorable photographs into highly sought-after digital tokens that can be acquired by ardent followers. Nafter An online marketplace built for both creators and fans, the web app is refreshingly simple to use: all influencers need to do is take a photo with their smartphone, mint it as an NFT, post it on Nafter, then share and sell to the highest bidder. Keen fans can also “stake” on a creator’s profile in order to qualify for access to exclusive content by that creator; stakers also get to earn additional NAFT tokens into the bargain. This governance token enables 0% on Nafter transactions and also allows holders to vote on platform upgrades. Interestingly, Nafter content creators – models, fashion bloggers, photographers, fitness gurus – can customize who can see their NFTs, choosing between making posts public or for collectors/stakers only. Essentially, the platform lies at the intersection of Instagram, Defi, and NFTs, representing a new monetization strategy for influencers the world over. Opulous is another newly-launched NFT platform that leans on defi – decentralized loans, specifically. Designed to alter the way musicians access the funding they need, Opulous also represents a launchpad for the release of copyright-backed music NFTs. Opulous With the likes of Kings of Leon and Aphex Twin having already proven the music-as-NFT use case, Opulous has partnered with Binance for a series of exclusive drops featuring work from artists including Lil Yachty and Kyle. Products in the pipeline include defi loans backed by future royalties, which will allow musicians to forward-plan production without relying on record labels. Within the Opulous ecosystem, artists earn royalty revenue directly from copyright shares, giving them a passive income and providing something the music industry sorely lacks – transparency. And lest you think Opulous is a shameless music-NFT cash-in, it was actually founded by Lee Parsons, the boss of music distribution platform Ditto Music. Voice NFTs aren’t, on the face of it, the most environmentally-friendly commodities. After all, the vast majority are built on Ethereum – an energy-intensive Proof-of-Work blockchain with a considerable output. On a more positive note, Ethereum plans to transition to greener Proof-of-Stake in the near future – and there are dedicated NFT platforms tackling the problem in the here and now. Step forward, Voice. is an environmentally-conscious NFT platform built on EOSIO, one that specializes in the creation of carbon-neutral NFTs which are free to mint for all creators. Currently in private testing – but scheduled for a public beta launch later this summer – Voice is on a mission to empower creatives in multiple creatives. To that end, it has teamed up with leaders in arts and culture to launch an NFT Residency through which creative minds can connect with true fans. Voice “Our residency brings emerging artists into the fold by partnering them with internal technologists to leverage our shared experience and create digital collectables, deep in thought and practice,” says William Anderson, VP of Engineering at Voice. Curators of the Residency in question, incidentally, include cultural commentator Misan Harriman, data protection expert Brittany Kaiser, 3D Instagram artist Chad Knight, and Paddle8 co-founder Alexander Gilkes. We expect we’ll be hearing lots about Voice in the coming months. Bitski NFT marketplaces might seem kind of ubiquitous, but has some serious muscle behind it: Jay-Z, Serena Williams and the Winklevoss brothers contributed to its latest funding round led by Andreesen Horowitz, which raised $19 million. Bitski Described as “Shopify for NFTs,” the San Francisco startup does what you’d expect a marketplace to do: it enables users to create, sell and own unique digital content. That content can include everything from custom AR skins for use in various gaming apps, art drops with built-in royalty schemes, golden tickets that grant holders early access to exclusive content, and even NFTs representing a real-world item. Bitski is free until the moment you create an NFT, whereafter you can choose between three subscription tiers, easily mint and sell NFTs from your own online storefront, and access round-the-clock customer support. Users, meanwhile, can bid on and sell items at their leisure, interacting with emerging and established artists and accessing a range of nifty tokenized goods. Anima Users tend to be able to interact with NFTs via their digital wallets, but as time goes on, such tokens will, and indeed already are acquiring more functionality. , for example, combines the worlds of non-fungible tokens and Augmented Reality (AR), with tokens on its platform usable in what it calls the “camera metaverse.” Anima Having recently raised $500,000 from investors including Coinbase, Anima is preparing to launch its Consensys Palm-based marketplace later this month and has already dropped a few NFTs on Nifty Gateway. Augmented Reality NFTs theoretically enable users to interact with them as they would in the real world – thus, you could mount an AR NFT of a painting on your very own (virtual) living room wall. The potential for bringing unique digital art objects into an immersive AR environment is enormous, and it’s easy to imagine the domino effect when VR and AR really starts motoring in the years ahead: Apple is rumored to have hundreds of employees working on VR/AR projects, and an AR product could be only a year away. With so many platforms busy building, it’s easy to forget that NFTs are a new and emerging technology. The mind boggles at how the landscape might look in a year or two. In any case, don’t expect the NFT hype to die down anytime soon. Disclaimer: This material is not sponsored by any organization mentioned in the article.

5 New NFT Platforms Riding Crypto’s Latest Wave

This paper is available on arxiv under CC 4.0 license. Authors: (1) Pierre Colombo, Equall, Paris, France & MICS, CentraleSupelec, Universite Paris-Saclay, France; (2) Victor Pellegrain, IRT SystemX Saclay, France & France & MICS, CentraleSupelec, Universite Paris-Saclay, France; (3) Malik Boudiaf, ÉTS Montreal, LIVIA, ILLS, Canada; (4) Victor Storchan, Mozilla.ai, Paris, France; (5) Myriam Tami, MICS, CentraleSupelec, Universite Paris-Saclay, France; (6) Ismail Ben Ayed, ÉTS Montreal, LIVIA, ILLS, Canada; (7) Celine Hudelot, MICS, CentraleSupelec, Universite Paris-Saclay, France; (8) Pablo Piantanida, ILLS, MILA, CNRS, CentraleSupélec, Canada. Table of Links Abstract & Introduction Related Work API-based Few-shot Learning An Enhanced Experimental Setting Experiments Conclusions Limitations, Acknowledgements, & References Appendix A: Proof of Proposition Appendix B: Additional Experimental Results 2 Related Work 2.1 Few-shot learning in NLP Numerous studies have tackled the task of FSL in Natural Language Processing (NLP) by utilizing pre-trained language models (Devlin et al., 2018; Liu et al., 2019b; Radford et al., 2019; Yang et al., 2019). These methods can be classified into three major categories: prompt-based, parameter efficient tuning, and in-context learning. Prompt-based FSL: Prompt-based FSL involves the use of natural language prompts or templates to guide the model to perform a specific task (Ding et al., 2021; Liu et al., 2023). For example, the seminal work (Schick and Schütze, 2020a) proposed a model called PET, which uses a pre-defined set of prompts to perform various NLP tasks as text classification. They also impose a choice of a verbalizer which highly impacts the classification performances (Cui et al., 2022; Hu et al., 2021a). However, recent studies have questioned the benefits of prompt-based learning due to the high variability in performance caused by the choice of prompt (Liu et al., 2022). To address this issue, researchers have proposed prompt tuning which involves a few learnable parameters in addition to the prompt (Lester et al., 2021). Nevertheless, these approaches face limitations when learning from API: (i) encoder access for gradient computation is infeasible (as in R1), (ii) prompting requires to send data and label which raises privacy concerns (as in R3), and (iii) labeling new points is time-consuming (see in R3) and expensive due to the need to send all shots for each input token[1]. These methods, such as adapters (Houlsby et al., 2019; Pfeiffer et al., 2020), keep most of the model’s parameters fixed during training and only update small feedforward networks that are inserted within the larger model architecture. A recent example is T-FEW (Liu et al., 2022), which adds learned vectors that rescale the network’s internal activations. Additionally, it requires a set of manually created prompts for each dataset making it hard to use in practice. Relying on parameter-efficient fine-tuning methods with an API is not possible due to the need to compute gradients of the encoder (as per R1) and the requirement to send both the labeling schema and the labels, which violates R3. Parameter-efficient fine-tuning. In-context learning models are models that utilize input-to-output training examples as prompts to make predictions, without any parameter updates (Wei et al., 2022). These models, such as text-davinci, rely solely on the provided examples to generate predictions, without any additional training. However, a significant drawback of this approach is that the user must supply the input, label examples, and task description, which becomes prohibitively expensive when the number of classes or shots increases, is slow (Liu et al., 2022) (R2) and raises data privacy concerns (as highlighted in R3). Additionally, the inability to reuse text embeddings for new tasks or with new labels without querying the model’s API limits practicality and scalability, making reusable encoding unfeasible for in-context learning models [2]. In Context Learning (ICL). or quite long stood as the de-facto paradigm for FSL ((Snell et al., 2017; Rusu et al., 2019; Sung et al., 2018b; Lee et al., 2019; Raghu et al., 2019; Sun et al., 2019a)). In meta-learning, the objective is to provide the model with the intrinsic ability to learn in a data-efficient manner. For instance, MAML ((Finn et al., 2017a; Antoniou et al., 2018)), arguably the most popular meta-learning method, tries to train a model such that it can be fine-tuned end-to-end using only a few supervised samples while retaining high generalization ability. Unlike the three previous lines of work, meta-learning methods operate by modifying the pre-training procedure and therefore assume access to both the training data and the model, which wholly breaks both R1 and R3. 2.2 Inductive vs transductive learning Learning an inductive classifier on embeddings generated by an API-based model, as proposed by (Snell et al., 2017), is a common baseline for performing FSL. This approach is prevalent in NLP, where a parametric model is trained on data to infer general rules that are applied to label new, unseen data (known as inductive learning (Vapnik, 1999)). However, in FSL scenarios with limited labeled data, this approach can be highly ambiguous and lead to poor generalization. Transduction offers an attractive alternative to inductive learning (Sain, 1996). Unlike inductive learning, which infers general rules from training data, transduction involves finding rules that work specifically for the unlabeled test data. By utilizing more data, such as unlabeled test instances, and aiming for a more localized rule rather than a general one, transductive learning has shown promise and practical benefits in computer vision (Boudiaf et al., 2020, 2021; Ziko et al., 2020). Transductive methods yield substantially better performance than their inductive counterparts by leveraging the statistics of the query set (Dhillon et al., 2019). However, this approach has not yet been explored in the context of textual data. [1] The cost of API queries is determined by the number of input tokens that are transmitted. [2] Furthermore, as the number of considered classes increases, the fixed size of the transformer limits the number of possible shots that can be fed to the model. Previous studies have often neglected this limitation by focusing on a few numbers of labels.

Transductive Learning for Textual Few-Shot Classification: Related Work

This paper is available on arxiv under CC 4.0 license. Authors: (1) Michael Günther, michael.guenther; (2) Jackmin Ong, jackmin.ong; (3) Isabelle Mohr, isabelle.mohr; (4) Alaeddine Abdessalem, alaeddine.abdessalem; (5) Tanguy Abel, tanguy.abel; (6) Mohammad Kalim Akram, kalim.akram; (7) Susana Guzman, susana.guzman; (8) Georgios Mastrapas, georgios.mastrapas; (9) Saba Sturua, saba.sturua; (10) Bo Wang, bo.wang; (11) Maximilian Werk, maximilian.werk; (12) Nan Wang, nan.wang; (13) Han Xiao, han.xiao}@jina.ai. Table of Links Abstract & Introduction Related Work Training Process Overview Backbone Pre-training Fine-Tuning for Embeddings Evaluation Conclusion & References Appendix 4 Backbone Pre-training For the backbone training, we introduce a novel transformer model. Although its architecture is akin to the BERT model proposed by [Devlin et al., 2019], we implement several modifications to enhance its ability to encode extended text sequences and to generally bolster its language modeling capabilities. For the training process, we largely adopt the approach described in [Liu et al., 2019a], incorporating additional performance optimizations. 4.1 Model Architecture For the selfattention mechanism within the attention blocks, we adopt the Attention with Linear Biases (ALiBi) approach [Press et al., 2022]. ALiBi forgoes the use of positional embeddings. Instead, it encodes positional information directly within the self-attention layer by introducing a constant bias term to the attention score matrix of each layer, ensuring that proximate tokens demonstrate stronger mutual attention. While the original implementation was designed for causal language modeling and featured biases solely in the causal direction, such an approach is not compatible with the bidirectional self-attention inherent in our encoder model. For our purposes, we employ the symmetric encoder variant where attention biases are mirrored to ensure consistency in both directions[3] . Figure 1 depicts the computation of attention scores within the multi-head attention heads. Each head’s scaling value, mi , out of the total n heads, is derived using Equation (1). Attention with Linear Biases: For the feedforward sublayers within the attention blocks, we adopt Gated Linear Units (GLU), originally introduced in [Dauphin et al., 2016]. They’ve demonstrated performance enhancements when incorporated into transformers [Shazeer, 2020]. For the small and base models, we employ the GEGLU variant, which leverages the GELU activation function for the GLU. Conversely, for the large model, we utilize the ReGLU variant with the ReLU activation function. This choice was driven by our observation that training the large model with GEGLU, despite its promising initial MLM accuracy, was unstable. Gated Linear Units: Regarding Layer Normalization [?], we align with the post-layer normalization approach from [Vaswani et al., 2017] in our attention blocks. Preliminary tests with pre-layer normalization, as mentioned in [Shoeybi et al., 2019] and [Nguyen and Salazar, 2019], didn’t enhance training stability or performance. Consequently, we opted not to integrate it into our model. Layer Normalization: 4.2 Full-Text Datasets for Pre-training For the pre-training phase, we leverage the English “Colossal, Cleaned, Common Crawl (C4)” dataset [4] , encompassing approximately 365 million text documents harvested from the web, summing to around 170 billion tokens. As delineated in [Raffel et al., 2020], the C4 dataset is a refined iteration of Common Crawl, utilizing heuristics for cleanup and language recognition, retaining solely English content. As a result, our models are monolingual and tailored exclusively for English texts. The purification process also encompasses the removal of webpages hosting inappropriate content. We reserve 1% of the dataset for evaluating validation loss and the accuracy of the masked language modeling (MLM) task. 4.3 Training Algorithm Our model’s pre-training revolves around the masked language modeling objective, excluding the next sentence prediction (NSP) task due to its perceived limited contribution to downstream task performance [Liu et al., 2019a]. We mask 30% of the input tokens randomly, employing whole word masking [Devlin et al., 2019], and condition the models to infer these masked tokens. Of these masked tokens, 80% are substituted with the [MASK] token, 10% with a random token, and the remaining 10% stay unaltered. Given our model’s reliance on ALiBi attention [Press et al., 2022], training position embeddings becomes unnecessary. This allows us to pre-train more efficiently on shorter sequences and adapt to longer sequences in subsequent tasks. Throughout our pre-training, we operate on sequences capped at 512 tokens in length. Diverging from the methods in [Devlin et al., 2019] and [Liu et al., 2019a], our sequences originate from individual documents without any multi-document packing. Furthermore, we refrain from sampling multiple sequences from a singular document. For each document, we exclusively consider its initial 512 tokens, truncating any excess. Given our consistent global batch size of 4096, each batch, due to its varying sequence length, contains a unique number of masked tokens when calculating loss. Mirroring the optimization strategy of RoBERTa [Liu et al., 2019a], we employ the AdamW algorithm [Loshchilov and Hutter, 2017], characterized by parameters β1 = 0.9, β2 = 0.98, ϵ = 1e − 6, a weight decay of 0.01, dropout set at 0.1, and attention dropout also at 0.1. Our learning rate schedule is linear, starting at 0 and peaking at a rate of η post 10, 000 steps. Here, the values of η are designated as 1e−3, 6e−4, and 4e−4 for the small, base, and large models respectively. A linear decay to zero ensues after reaching the 100, 000 steps threshold. Optimizer: We resort to FP16 dynamic mixed precision [Micikevicius et al., 2018] for pre-training our models, facilitated by the DeepSpeed software package [Rasley et al., 2020]. Our preliminary tests using BF16 revealed unsatisfactory performance metrics, both in MLM accuracy and the downstream GLUE tasks. Mixed precision training: [3] https://github.com/ofirpress/attention_with_ linear_biases/issues/5 [4] https://huggingface.co/datasets/c4

JINA EMBEDDINGS 2: 8192-Token General-Purpose Text Embeddings: Backbone Pre-training

Moonshot Commons, a global Generation-Z Web3 builder community backed by 10+ top-tier investors, successfully concluded its winter hackathon themed “Rethink, Restate, and Recharge.” The winter hackathon was the 7th Hackathon that Moonshot Commons has hosted, as the Web3 builder community celebrates its second anniversary in January. Speaking on the occasion, the founding team said, “even amidst crypto winter, Moonshot is still determined to support smart, scrappy, and globally-minded builders, founders, and researchers in the crypto space.” More than 1000 participants, in 216 teams, building in fields such as infrastructure, SocialFi, open finance, and DAO tooling responded, resulting in 22 projects being crowned and demo-ed their projects to 50+ participating VCs and receiving credits and prizes from sponsors and partners like , , , , , , and . All of them also have the opportunity to receive post-hackathon incubation support as batch 5 members of Moonshot’s founder community. KCC Mask Network Mirror World Chainbase Signum Capital UOB Vnetures AWS From Team Selection to Apollo Demo Day The Hackathon was conducted in three weeks - from Dec. 19, 2022, to Jan. 9, 2023. Starting with opening addresses from speakers including partner Xing Liu, CEO Evan Shapiro, Professor Kani Chen, and Founder Suji during the event inauguration, hackers were provided with “closed-door workshops” led by industry mentors, cohort office hours organized by Moonshot community members, and personalized pitch preparation sessions supported by top-tier investors. On Jan. 14, 2023, 22 teams were selected to enter the final battlefield “Apollo Demo Day” and showcased their creativity and innovation to 50+ VCs, funds, and media companies from across the globe. Sequoia China Mina Protocol HKUST Mask Network Unlike many hackathons which are usually backed by a single sponsor and require hackers to only build on the sponsored network, Moonshot's biannual hackathons aim to provide an open platform for Web3 project development and thus do not limit participants to a specific chain. The founding team believes that it is far more important to onboard the next generation of developers to the Web3 world rather than fight over which chain they build on or which solution they adopt to accelerate project growth. Kevin, the Founder of Moonshot Commons, expands upon the team’s vision to Hackernoon: “According to a , the number of monthly active Web3 developers reached over 23,300 as of December 2022, compared to over 20 million Web2 developers in the world. Through our hackathons and other initiatives, we want to break down the barriers for Web2 developers and establish Moonshot as the gateway to the Web3 world.” Jan. 16 report from Electric Capital One way that Moonshot supports participating projects is by hosting “closed-door workshops” led by industry mentors. This winter, Moonshot saw strong and active engagement from its founder community and brought 30 of them to interact with fellow hackers live. Sample topics and speakers include: “Cold start and GTM strategies for Web3 applications” by Founder Charles Galxe “Product design of Web3 decentralized application layer” by Founder Chess Quest3 “Opportunities and applications of zero-knowledge proof” by Co-Founder Victor Manta Network “The future and opportunities of the Move ecosystem” by Founder Wendy Momentum Safe “The spread of Web3 innovation in a decentralized world” by Founder Wu Xiao ChainIDE “Web3 community building and marketing promotion” by Founder Wilson Cyberconnect Following three weeks of intense hacking, learning, and networking, Moonshot’s “Apollo Demo Day” took place on Jan. 14, 2023. The event featured an opening address by Hash Global founder KK and a closing address by ByteTrade founder Dr. Lu, in addition to active participation and live Q&A from representatives of 50+ VCs including Sequoia China, , , , , and . HashKey Zhen Fund IOSG Matrix Partners China Redpoint Ventures Meet the Top Project Teams These 22 teams emerged victorious: an NFT-gated messaging app Chataverse: a UGC platform that combines 3D and AI, allowing users to create, share, and monetize virtual environments and AR decorations with ease ST World (System Terminal): a decentralized organization and community management tool based on the ENS subdomain Org3: a decentralized crowdfunding ecosystem governed by $KOM token Kommunitas: a decentralized open science community powered by blockchain and AI Symposium Lab: a decentralized NFT AMM, enabling instant NFT swaps and better price discovery Ladder Protocol: privacy-focused zkVM for developers Eigen Network: a Machine-Fi fitness-to-earn application project Caldance: helps Web3 builders create user-owned professional identities and warm intro networks using SBTs and verifiable credentials Lewk: a decentralized Web3 metaphysics platform Ascendant Network: a decentralized NFT marketplace that supports leverage trading, Share2Earn, and Play2Earn Winner: a next-generation on-chain podcasting platform that aims to make the spread and evolution of ‘sound civilization’ more free and diverse xCast: Kindle in the Web3 era - come to The Reader and invest in the next “The Three-Body Problem” The Reader: easy-to-use next-generation digital wallet ZK MPC Wallet: trust-worthy and security measurement platform for Web3 projects Descrypto: a Web3 intelligent investment research community MemeBook: : a Web3 marketing and loyalty management platform based on account abstraction and brand NFT Tristan Alliance brings beverage brands and consumers together via NFTs with gamification and socialization features to build a digital community centered around beverages DrinkUP: : provides gamers with a high-quality decentralized game social open platform to help game producers gather players and users Gameland a disruptive way to interact with an array of Web3 Defi dapps Avault: an SBT-based open social network Discoverse: provide users with clear and transparent dealmaking derivatives trading Scale Protocol: a non-ownership-transferred, collateral-free, protocol Ghost NFT: allows anyone to send subjective, relational, or programmable SBT based on social layer protocol Solas: Find details about all Moonshot Commons’ 2022 Winter Hackathon winners and their video pitches in the . If interested in any of the projects above, please fill out this or reach out to to be connected. pamphlet Typeform founders@moonshotcommons.com About Moonshot Commons , based in Hong Kong, Singapore, and New York, we’re a global Gen Z Web3 builder community backed by HashKey Capital, ChainIDE, Mask Network, Hash Global, Zhen Fund, and more. Within two years, our founders raised over $100 million from VCs — with many more launching soon. Moonshot Commons

Hackers Shine: Moonshot Commons Web3 Hackathon Concludes Successfully

Hackers Shine: Moonshot Commons Web3 Hackathon concluye con éxito

Les pirates brillent : le hackathon Moonshot Commons Web3 se termine avec succès

हैकर्स शाइन: मूनशॉट कॉमन्स वेब3 हैकथॉन सफलतापूर्वक संपन्न हुआ

Hackers Shine: Moonshot Commons Web3 Hackathon が成功裏に終了

Hackers brilham: Moonshot Commons Web3 Hackathon conclui com sucesso

Hackers Shine: Moonshot Commons Web3 Hackathon kết thúc thành công

黑客大放异彩：Moonshot Commons Web3 黑客马拉松圆满结束

Hi Kevin, welcome to our series “Behind the Startup.” Would you please tell us about yourself and the story behind Metis? Ishan Pandey: My name is Kevin, co-founder of Metis. I have over five years of experience in product development, and I have studied DAO, governance, and decentralized collaboration since 2018. That is when I met Elena and Yuan, my other two co-founders. In the beginning, we hoped to solve the issues of decentralized and distributed collaborations happening more and more frequently in the physical world. Later, we found out that we will need a robust infrastructure to support the decentralized business running on the blockchain. The current Layer1 blockchains are hard to handle, and we can only support these kinds of collaborations on Layer2, and that’s the beginning of the Metis project. Kevin Liu: Interoperability and the new Layer 2 chain are expected to revolutionize the crypto space. How does the layer 2 chains operate? Would you please provide a high-level overview of the same? Ishan Pandey: Layer 2 refers to a wide range of scaling solutions(rollups, validium, plasma, state channels, etc.) designed to help scale your application by handling transactions off the Ethereum mainnet (layer 1), while taking advantage of the robust decentralized security model of mainnet. Metis is in the rollup battlefield, and generally speaking, rollups are solutions that perform transaction execution outside the main Ethereum chain (layer 1), but post transaction data on the layer. Kevin Liu: As transaction data is on layer 1, this allows rollups to be secured by layer 1. Inheriting the security properties of layer 1, while performing execution outside of layer 1, is a defining characteristic of rollups. Three simplified properties of rollups are: Transaction execution outside layer 1 Data or proof of transactions is on layer 1 A roll-up smart contract in layer 1 that can enforce correct transaction execution on layer 2 by using the transaction data on layer 1 Rollups require to stake a bond in the rollup contract. This incentivizes operators to verify and execute transactions correctly. “operators” Can you tell us about some of the existing drawbacks with the layer 2 protocol and how can they be effectively addressed and resolved? Ishan Pandey: For Layer 2 Optimistic Rollups, the common criticisms are long wait times for on-chain transactions due to potential fraud challenges(actually it is because of lack of incentives as we always assume that no one will do sth bad, and that is why it is called Optimistic Rollup), and some people also criticize that the standard layer 2 design is usually very centralized. Many of these constructs duplicate a centralized structure from a single sequencer, relying on the verification mechanism to deter malicious players from fraudulent behaviours. Kevin Liu: The decentralized design includes multi Virtual Machines, Sequencer Pools to eliminate the bottleneck of one virtual machine and one sequencer. Metis introduces a Ranger’s system to incentivize the fast validators with Metis token mining rewards to solve the problem of long validation time, leveraging economic ways to speed up the transaction validation time. The DAO legislation is to take effect from July 2021. Please tell us a little bit about how blockchain startups view this legislation that governs decentralized autonomous organizations? Ishan Pandey: Currently, a big obstacle facing DAOs is the worry that any member of the organization could be held personally liable for the actions of the DAO. The new law permits DAOs to incorporate as limited liability companies – a corporate structure whereby the company members are not held personally liable for the debts and liabilities of the company. So this formal legal framework is a big step for the crypto industry and may solve the issue of member liability. It also brings the possibility of connecting DAO with the real-world business, imaging a consultant DAO as a service provider to a big corporation. Kevin Liu: High Ethereum gas prices have consistently been among the most flagged issues within the Ethereum ecosystem. How can this very pertinent issue be tackled to promote the overall growth of the system? Ishan Pandey: That’s why we need layer 2 solutions to help scale Ethereum, lower the cost and increase the transaction speed. With Metis Layer 2, we feature the 1 cent transaction cost and 1-second transaction speed on Layer 2 to solve the most flagged issues. Besides, storage on Ethereum is also super expensive, so integrating with IPFS or Swarm on Layer2 is also the option for projects on Ethereum to lower down the operating costs. Kevin Liu: The Bitcoin Mining Council (BMC) has recently debuted as an open platform for Bitcoin miners in the wake of an outcry over the volume of fossil fuel-based energy used to mine the cryptocurrency. Do you think this council will really be able to make a difference in terms of protecting the environment? Further, what are your views on bitcoin’s electricity consumption? Ishan Pandey: First, Any good deeds or initiatives toward protecting the environment is highly appreciated and welcomed. We can find that more and more countries or states have offered various solutions to speed the transition from fuel-based energy to clean energy, like wind, solar, hydro and even geothermal. Making people realize this environmental issue is a good start to solve it anyway. The energy consumption to generate bitcoin is a reasonable way to create something valuable. Many years ago, people also criticized the energy consumption of the internet, but see the progress that the Internet has brought to human beings. The energy consumption will generate more value than it consumes. Kevin Liu: There is a lot of competition within the DeFi sector. According to you, between Polkadot, Binance Smart Chain and Tron, which blockchain will win the race for the second position next to Ethereum? Ishan Pandey: It is still too early to tell. EOS was so popular back to the last bull run, and was claimed to replace Ethereum, but later turned out to be an almost dead blockchain with no solid projects and users. To race for the second position, the blockchain will need a solid infrastructure and the active involvement of community members. And it is not just the trading of tokens, but to build applications one by one, so it really takes time to see who will last to the end. Kevin Liu: El Salvador is now the world’s first nation to embrace bitcoin as legal tender. President Nayib Bukele applauded its potential to enable Salvadorans living abroad to send remittances home. From a regulatory standpoint, what are your views on this move, especially since the IMF has cited several legal concerns over making bitcoin a legal tender? Ishan Pandey: I do not doubt that more and more countries will take bitcoin as the reserve along the way, but taking bitcoin as the legal tender will need to solve KYC and AML from the regulatory perspective and also, the tax issues need to be addressed. To make it work, I think there will be a trade-off between purely decentralization and centralized administration. El Salvador will need to set up an official reserve of Bitcoin and also a whole system to recognize, track and evaluate the bitcoin sending back from overseas. Kevin Liu: Recently, all crypto miners in China’s Qinghai Province have been ordered to shut down amidst China’s attempt at implementing strict crypto regulations. In your opinion, what impact will this have on the crypto industry globally? Ishan Pandey: In my opinion, the decentralization of mining power is a good thing for the crypto industry in the long run. If large mining pools or players control 65% of the mining power, it does not coincide with the decentralization spirit of crypto either. Kevin Liu: : What are your views on NFT art and the valuation of NFT-based artwork? : NFT art is only at the beginning of a global and long term trend. NFT will speed up the circulation and trade of artworks, but now the users are still in a small circle of crypto users or some early adopters. So there is still a long way to go. For the valuation of NFT-based artwork, I think most of them are overvalued, which is used to attract the public’s attention. IMO, with blockchain as the infrastructure, DAO enabled the community to participate. There will be many different styles of NFT artwork emerging, not just paintings or music. Ishan Pandey Kevin Liu Disclaimer: The purpose of this article is to remove informational asymmetry existing today in our digital markets by performing due diligence by asking the right questions and equipping readers with better opinions to make informed decisions. The material does not constitute any investment, financial, or legal advice. Please do your research before investing in any digital assets or tokens, etc. The writer does not have any vested interest in the company. Ishan Pandey.

"Rollups Incentivize Operators to Verify and Execute Transactions Correctly." - Kevin Liu

From Tuesday March 13 through Wednesday March 14, the 5th annual will bring together hackers, creators, makers, and coders to converge to solve problems, create new tools, and push the boundaries of existing tech across entertainment media. SXSW 24 Hour Hackathon After receiving hundreds of applications, we’ve narrowed the field to the top 120 hackers. It’s going to be fun. While the field is mostly set, we’re still reviewing all new applications. . Apply here “When you think of SXSW, depending on who you are you either think of the best new music, technology, or movies,” said . “As a polymath myself, I co-created the SXSW Hackathon to be the blender where all of the elements of SX are united as one and the incubator to give the winning teams SXSW itself as their initial and very fertile testing ground for real world users.” Travis Laurendine “This year as the ultimate nod to the importance of innovation at the intersection of technology and entertainment, we have some of the most valuable companies in the country sponsoring and sending engineers to help participants build things for artists and their consumers to use,” Travis continued. “I can’t wait to see what these super star developers build on these consumer platforms that translate to over $1 trillion in market cap. Especially when they see what’s in the new sandbox that Capitol Records is bringing into the mix and the other music, film and API surprises we have waiting for them!” At HackerNoon, we’re proud to be a media sponsor for such an exciting event. We’ll have an area at the event, where you can tell us your tech story. . Looking forward to meeting you there :-) Can also DM me 2018 SXSW Hackathon Mentors Proud to announce the mentors for the Hackathon and Incubator are: (Universal) Lily Chen (Leansquare/ Wallfornia Music Tech) Gerome Vanherf (Ty Roberts Innovation) Ty Roberts (YG Entertainment) Danny Lee (Founders Embassy) Andee Gardiner (Reven8te/Ticket Galaxy) Dano Leman (Emojam). Louise-Marie Marguet 2018 SXSW Hackathon Judges The judges* for Hackathon are: (Universal Music) Tuhin Roy (Floodgate) Ryan Walsh (Gen Z Whisperer) Tiffany Zhong (AUSUM Ventures) Jeremy Gardner (XLIVE) Waco Hoover (Liebenson Law) Jeff Liebenson (Earmilk) David Sikorski (Scale API) Lucy Guo (HackerNoon) David Smooke *previously announced in . Join Us at The SXSW 24 Hour Hackathon 2018 SXSW Hackathon Sponsors USAA, known for its innovative approach to bringing banking and insurance to its members, is joining us for the SXSW Hackathon as the presenting sponsor. . USAA Alexa is a cloud-based voice service from Amazon. Alexa is the brain behind Amazon Echo and other Alexa-enabled devices. . Amazon Alexa Amazon Web Services (AWS) is a secure cloud services platform, offering compute power, database storage, content delivery and other functionality to help businesses scale and grow. Millions of customers are currently leveraging AWS cloud products and solutions to build sophisticated applications with increased flexibility, scalability and reliability. Amazon Web Services. Capitol Music Group (CMG) is comprised of Capitol Records, Virgin Records, Motown Records, Blue Note Records, Astralwerks, Harvest Records, Capitol Christian Music Group, and CMG’s independent distribution division, Caroline. . Capitol Music Group . ConsenSys is a global formation of technologists and entrepreneurs building the infrastructure, applications, and practices that enable a decentralized world. ConsenSys Manage web and mobile media assets with Cloudinary, the leading cloud service: image and video uploa . Cloudinary d, storage, manipulation, optimization, digital asset management and delivery. Additional partners are Devpost and HackerNoon . :-) Until next time, don’t take the realities of the world for granted. Kind Regards, David Smooke . While the field is mostly set, we’re still reviewing all new applications. . P.S Apply here Here are SXSW panels and events I’m excited about: P.P.S. How to Create Necessary, Targeted, Authentic Media Crunch by Crunch Fest Two-Day Crypto Summit Coming to SXSW 2018, Featuring Women in Blockchain Conference — ‘New Girls on the Block.’ The Art of Inclusivity in a Politically Divided US How to Build a Company Where the Best Ideas Win Out The Persistence of Patent Trolls in Tech AI: Ready to Disrupt Experience Design? Modern-day Publisher Models: Beyond Advertising Animation in UX: Subconscious Influence of Motion THIS IS US Season 2 Finale Episode (w/ Cast Members) War on Platforms: Is the Medium Still the Message? What User Experience Exposes About Your Culture Can AI Soothe the Savage Comment Section? From AI to EI: Empathy is the New Tech Superpower Why Machine Learning is the Next Frontier for Art The Bill Murray Stories: Life Lessons Learned From A Mythical Man Social Media & Social Good: Creators to The Rescue Content Creation in the Age of AI Phil Hellmuth Jr. Book Signing Social Media + Social Causes Meet Up Driving Audience: If You Build It, They Will Not Come ICO Alternative Financing for Startups Free Radical: Chelsea Manning with Vogue’s Sally Singer Building Communities: URL & IRL

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DOE v. GITHUB Court Filing, retrieved on January 26, 2023 is part of . You can jump to any part in this filing . This part is 17 of 21. HackerNoon’s Legal PDF Series here MEMORANDUM OF POINTS AND AUTHORITIES IV. ARGUMENT C. Plaintiffs’ Claims Fail for Reasons Specific to Each Claim. 7. Plaintiffs Fail to Adequately Plead A Violation of the CCPA. Plaintiffs’ claim under the CCPA suffers from numerous pleading defects. Plaintiffs lack statutory standing, and they failed to provide the required written notice to the OpenAI Entities prior to filing this complaint. Even if Plaintiffs satisfied these threshold requirements, the CCPA’s limited private right of action does not cover the alleged conduct. To the extent any of these allegations are actionable, Plaintiffs also failed to allege facts showing that the OpenAI Entities disclosed personal information protected by the CCPA. As an initial matter, the named Plaintiffs cannot satisfy the statutory requirements for a CCPA claim. Out-of-state plaintiffs lack standing to assert a claim under the CCPA. Cal. Civ. Code § 1798.140(i) (defining “consumer” under the CCPA as “a natural person who is a California resident”); see Hayden v. Retail Equation, Inc., No. SACV2001203DOCDFM, 2022 WL 2254461, at *5 (C.D. Cal. May 4, 2022) (concluding that “CCPA claims brought by out-ofstate Plaintiffs [] fail because the CCPA does not apply to non-California residents”). Here, Doe 3 and Doe 4 are not California residents. (See Compl. ¶¶ 19-20.) Moreover, Plaintiffs failed to comply with the requirement to provide the OpenAI Entities with written notice of the alleged CCPA violations prior to filing the complaint. Section 1798.150(b) states that “prior to initiating any action” under the CCPA, the customer must provide “written notice identifying the specific provisions [that] have been or are being violated.” Cal. Civ. Code § 1798.150(b). No OpenAI Entity received such notice, and the complaint does not allege otherwise. The CCPA claim also should be dismissed because it provides only a limited private right of action: a consumer must allege that their “nonencrypted and nonredacted personal information” was “subject to an unauthorized access and exfiltration, theft, or disclosure as a result of a business’s violation of the duty to implement and maintain reasonable security procedures and practices appropriate to the nature of the information.” Cal. Civ. Code § 1798.150(a)(1). No cause of action exists for “violations of any other section of [the CCPA].” Cal. Civ. Code § 1798.150(c). It is well-settled that “a statute creates a private right of action only if the statutory language or legislative history affirmatively indicates such an intent.” Lil’ Man In the Boat, Inc. v. City and Cnty. of San Francisco, No. C17-CV-00904-JST, 2018 WL 4207260, at *3 (N.D. Cal. Sept. 4, 2018) (cleaned up). The OpenAI Entities’ alleged failures to provide (i) an opt-out notice, (ii) a clear and conspicuous opt-out link, (iii) a right to deletion, and (iv) a right to access personal information, are not actionable because the CCPA unambiguously reserved enforcement of these provisions to the California Privacy Protection Agency. See Cal. Civ. Code § 1798.155(a). Finally, Plaintiffs’ vague and conclusory allegations regarding the OpenAI Entities’ security practices fail to state a claim under the CCPA. “[P]lausibility pleading standards are especially important in cases like this, where the Defendant faces the ‘potentially enormous expense of discovery’ if the Court denies [a] motion to dismiss.” Razuki v. Caliber Home Loans, Inc., No. 17cv1718-LAB (WVG), 2018 WL 6018361, at *2 (S.D. Cal. Nov. 15, 2018) (dismissing data breach claims). In the absence of allegations that show the OpenAI Entities’ security procedures and practices were deficient, Plaintiffs cannot state a CCPA claim. See Maag v. U.S. Bank Nat’l Ass’n, No. 21-cv-00031-H-LL, 2021 WL 5605278, at *2 (S.D. Cal. Apr. 8, 2021) (dismissing CCPA claim where plaintiff made unsupported allegations that “his PII was compromised because Defendant did not ‘implement and maintain security procedures and practices’ [and] ‘failed to effectively monitor its systems for security vulnerabilities’”); Anderson v. Kimpton Hotel & Rest. Grp., LLC, No. 19-CV-01860-MMC, 2019 WL 3753308, at *3-4 (N.D. Cal. Aug. 8, 2019) (dismissing complaint that was “devoid of facts” regarding the “inadequate securities measures” that purportedly caused plaintiff’s alleged injury). Here, Plaintiffs merely assert that the OpenAI Entities violated the CCPA by “collecting, maintaining, and controlling their customers’ sensitive personal information” and “engineering, designing, maintaining, and controlling systems that exposed their customers’ sensitive personal information” without specifying what type of “sensitive personal information” had been collected or exposed. (Compl. ¶ 233.) Plaintiffs further allege that the OpenAI Entities were “aware of Copilot’s propensity for revealing PII” and acted to “alter[] Copilot to force it to provide mock PII.” (Id. ¶ 234.) But these allegations do not state a claim under the CCPA’s narrow private right of action. Nowhere in the complaint do Plaintiffs allege that any OpenAI Entity was “subject to an unauthorized access and exfiltration, theft, or disclosure” (b) “as a result of [their] violation of the duty to implement and maintain reasonable and appropriate security procedures and practices.” Cal. Civ. Code § 1798.150(a). Nor do plaintiffs provide any factual support for their allegation that any PII (much less their own PII) had been “exposed” or “reveal[ed].” (Comp. ¶¶ 233-34.) Plaintiffs’ CCPA claim has nothing to do with a data breach or unauthorized access to defendants’ network—the crux of what this statute was designed to protect. Continue Reading . here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 4:22-cv-06823-JST retrieved on September 8, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. DocumentCloud.org

Details of the OpenAI Lawsuit: The Plaintiffs' Fail to Plead a Violation of the CCPA

Hi Elena Sinelnikova, welcome again to our series “Behind the Startup.” Please tell us about yourself and the story behind ? Ishan Pandey: Metis Years ago, my long-time friend Natalia Ameline and I started getting requests from friends of ours to explain what blockchain was. So we started having these little get-togethers over coffee in Toronto. Those get-togethers turned into larger local meetups. Those meetups started expanding to other places until eventually, they grew to cover 56(!) different countries around the world. From those humble beginnings, an organization called CryptoChicks was built, one of the world’s largest non-profit blockchain education and advocacy organizations. Elena Sinelnikova: As CryptoChicks grew, a large ecosystem emerged. Startup entrepreneurs started gathering within that ecosystem to figure out how to launch their own blockchain ideas; for instance, it was there that Stani Kulechov first started really running with his idea for a DeFi project, which today is AAVE, one of the largest DeFi projects in the world. It was also there that I met Yuan Su, a blockchain developer working for IBM Hyperledger who had been coding since age 6, and Kevin Liu, a serial founder, and incredibly smart product developer. The three of us loved the CryptoChicks idea of “blockchain for everyone,” so we decided to take that same idea and form our own company. That company became Metis. Three years later, Metis is building a hub for the entire Web3 economy in 3 stages: Layer 2 Ethereum scaling solution with transactions of a few seconds and a few cents; NO-CODE integration via smart contract templates, and a Decentralized Autonomous Company (DAC) infrastructure enabling both blockchain AND Web2 companies to build decentralized businesses ON-CHAIN, with all the functionalities of real-world enterprises and all the security and decentralization of the Ethereum blockchain. What are your views on rising Ethereum transaction fees? Further, is it making it difficult for blockchain startups to launch on Ethereum? Ishan Pandey: The Blockchain Trilemma is figuring out how to balance high security and decentralization with high scalability. Ethereum is great at the first two, but it struggles with scalability, as you mentioned. Currently, transactions on our Ethereum Layer 2 Rollup cost about $2; starting in Q1 2022, when we launch our new storage layer, those transactions will cost just a few cents. Elena Sinelnikova: You mention startups - it’s no coincidence that even though we just launched on mainnet 2.5 weeks ago, we already have more than 60 strategic partners, many of them being startups. With our no-code middleware, DAC infrastructure, and Builder Mining features complementing fast and cheap transactions and the security and decentralization of Ethereum, we are becoming the go-to place for startups looking to build and grow. Tell us about DAOs and regulations around DAOs? Ishan Pandey: Decentralized Autonomous Organizations are a great organizational structure in that they enable groups of people to band together and execute voting and governance functions in a decentralized way. At present, the progress has been slow and steady for DAO building, with more and more jurisdictions (such as the state of Wyoming in the U.S.) formally legalizing and welcoming DAOs. Elena Sinelnikova: What is a DAC? Further, how does it function, and what are its use-cases? Ishan Pandey: Metis is building a much more ambitious structure than DAOs: Decentralized Autonomous Companies (DACs). With DACs, every entity from a large Web2 company (imagine Nike) to a loosely affiliated group of enthusiasts (imagine you and 10 friends trading NFTs with each other) to something in between (a freelance staffing service like a Web 3/decentralized version of Fiverr or Upwork) can take advantage of our decentralized business templates and all of the features found in a Web2 company (ERP/CRM software, payroll management, Slack-like messaging platform) to run their entire operations right on the blockchain, with those fast and cheap transactions and secure, decentralized structure mentioned above! Elena Sinelnikova: Tell us about your views on Web 3 and how is it different from Web 2? Ishan Pandey: The biggest difference lies in governance. We are big believers in decentralization, to the point that we are the first Layer 2 platform to publish a complete decentralization roadmap, with a plan to hand 100% governance of our infrastructure over to our community (not our team!) by Q3 2022. Elena Sinelnikova: That one fundamental difference changes everything from how companies partner with each other to how teams operate on a day-to-day basis. The future of work is most definitely decentralized and most definitely focused on Web3. What are your views on Solana as an alternative to Ethereum for launching NFTs? Ishan Pandey: I mentioned the Blockchain Trilemma earlier. Solana sacrifices decentralization and security to make transactions cheaper. As long as its network continues to function, that’s great. Unfortunately, as we’ve seen recently, Solana has run into several network problems. When a major outage or, even worse, a major crash or loss of assets occurs, people will wish they’d turned to an environment in which they could, say, mint NFTs for just a few bucks and benefit from all the decentralization and security of Ethereum. Elena Sinelnikova: What are your views on Metaverse? Do you think it will break societal constructs like social media? Ishan Pandey: We are very excited about the growth of the Metaverse and about Metis’ ability to take Metaverse projects to the next level by including DACs! We see that trend and GameFi in general as being a huge driver of future blockchain growth, and more than that, just a really cool new idea for regular people to experience and enjoy. There are so many amazing Metaverse projects currently launching and expanding. Elena Sinelnikova: We are devoting significant investments and grants to the most promising MetaVerse projects, combining those incentives with the scalability, security, and decentralization that are our hallmarks, creating an ideal value proposition for MetaVerse projects looking to scale and build their business. According to you, what new trends are we going to see in the blockchain industry? Ishan Pandey: We believe the next big step is Web2 integration into Web3 ecosystems. Offering smart contract templates that serve as middleware, enabling anyone from overwhelmed blockchain developer teams to even Web2 companies with zero blockchain experience or expertise to hop onto the Metis network with just a few clicks. Combine that middleware with our DAC infrastructure, and we expect to onboard dozens and dozens of excellent Web2 partners from industries ranging from real estate to healthcare to gaming and much more in the weeks and months to come! Elena Sinelnikova: Disclaimer: The purpose of this article is to remove informational asymmetry existing today in our digital markets by performing due diligence, asking the right questions, and equipping readers with better opinions to make informed decisions.

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