Cy5.io | 3,805 followers on LinkedIn. Detect Security Issues &amp; Threats at Cloud Scale | At Cy5.io, we build cloud native security products that give our customers instant visibility, security insights and threat detection capabilities. Let our products manage your cloud security program while ...

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Cy5-SE (Cy5 NHS Ester) is a reactive dye for the labeling of amino-groups in peptides, proteins, and oligonucleotides. This dye requires small amount of organic co-solvent (such as DMF or DMSO) to be used in labeling reaction. This reagent is ideal for very cost-efficient labeling of soluble ...

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Cyanine5 (Cy5) is a bright, far-red-fluorescent dye with excitation suited for the 633 nm or 647 nm laser lines and is used for imaging, flow cytometry and genomics.

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Cyanine 5 (Cy5) is a fluorescent dye that belongs to the Cyanine family of synthetic polymethine dyes. Cy5 is reactive, water-soluble, and has an absorbance maximum of 649 nm and an emission maximum of 670 nm. It is available as both a phosphoramidite and an NHS ester, and is used to fluorescently ...

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ASX:CY5 - Investor presentation, announcements, cashflow waterfall chart, news, capital raise history, &amp; sector peers. Cygnus Gold Limited (CY5) operates as a mineral exploration and development company. The Company&#x27;s focus is on the exploration for economic gold deposits in the Southwest Terrane ...

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Specializing in Secondary Antibodies and Conjugates - For Western Blotting, IHC, ICC, Flow Cytometry, ELISA and other immunological applications.

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Below are the previous articles from Cygnus Gold (ASX: CY5): ... Get the latest stock news and insights straight to your inbox. ... By proceeding, you confirm you understand that we handle personal information in accordance with our Privacy Policy. For investors, getting access to the right information is critical. Stockhead’s daily newsletters make things simple: Markets coverage, company ...

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Cryptocurrency is a wild ride—a thrilling rollercoaster of highs and lows, with shocking surges followed by stomach-churning crashes. Bitcoin’s price is $52,000 as of this post! YouTube, Twitter, and Reddit tell you to make money now, FAST, and cash out with massive gains. What altcoin is about to explode? What's the best narrative for 2024? Sounds great. Who paid them for that? No time to panic Guard against the temptation of buying a significant amount of cryptocurrency at current prices, especially when history has shown us that better opportunities may lie ahead. This market always has downswings of 30 to 50% once or twice each year. Sometimes, these downswings can last months. Save your money for those times. Mark, You're telling us not to buy? It's the start of a massive bull market! What? I literally just said to buy some crypto. The bull market started in November 2022. It’s ok. You never get a bad price on bitcoin. No altcoin is worth its price today, but some will go much higher in the future. I'm a firm believer in the transformative power of blockchain technology and the potential of cryptocurrencies to revolutionize finance. I am even more bullish on the investment opportunity. That's something you can't get with any other asset class. However, I also recognize the importance of timing and strategic decision-making in this volatile market. Let's take a step back and look at the bigger picture. Keep it simple Bitcoin and other cryptocurrencies seem destined to reach new all-time highs any day now. It's easy to get caught up in the FOMO and feel the urge to jump on the bandwagon before prices climb even higher. Here's the thing: the crypto market is notoriously unpredictable, and what goes up must eventually come down. That's not to say that prices won't continue to rise in the short term. They very well might. There's just not that much more room to go up. That parabolic rise doesn’t have a lot of room left. Maybe 50% on bitcoin? 200% to 800% on altcoins? That’s less than you got last year and far less than you’ll get once the market settles down. Buying at current prices carries inherent risks, especially if you're investing a significant portion of your portfolio. Markets move in cycles. When you rush to buy at the booms, you risk being left holding the bag when they bust. Consider adopting a more measured approach. Wait for prices to drop. ”Consolidations” or “corrections,” as the traders say. When you do that, you position yourself to capitalize on better prices in the future. A drop to $35,000 wouldn't even break the uptrend we started in November 2022, but you’d get a lot more crypto for your money. One strategy to consider is dollar-cost averaging (DCA), where you invest a fixed amount of money at regular intervals regardless of market conditions. This reduces the risk of buying the peaks while also taking advantage of opportunities to accumulate crypto at lower prices during downturns. It's proven effective in all upward-trending markets. It's an objectively powerful way to invest. A man a plan a canal . . . Another approach that beats dollar-cost averaging without extra work or timing the market? . My plan With my plan, you’re up 850% at best, but more likely up about 110% with cash to spare. At worst, you’re even on your investment. On average, you get 30% more crypto with my plan than you get with dollar-cost averaging for the same amount that you put into the market, without trading or timing prices. The basic premise: buy low and grow. This seems backward. Traders would never buy an asset when it crashes. “Don't catch a falling knife.” Wait for a “break of resistance.” Oh well. The results speak for themselves. You can see for yourself in the chart that goes along with my plan. You may feel the urge to buy cryptocurrency at today's prices. With so much upside, you can wait for opportunities to come. A little patience and restraint can go a long way. You don't need to chase prices as they run away from you. Odds are, they’ll come back—if you’re patient. Available as a collectible NFT at . https://mirror.xyz https://mirror.xyz/0x9a6600c7B40801dda9A0Fa4E8DE7b1B99FE524a7/CY5DfVqBMJo_ZT_6Vbw2_xWS3tssY8oA0ZNx9KATlRQ?embedable=true Mark Helfman publishes the newsletter. He is also the author of three books and a top Bitcoin writer on and . Learn more about him in his and connect with him on or . Crypto is Easy Medium Hacker Noon bio Superpeer Tealfeed

Crypto’s Booming. Buy More Later. 

Leading a company as a founder and CEO can be exhausting. Between fundraising, hiring, listening to customers, and building products, it’s tough to make room to seek out advice from other experienced founders –– even when you know it’s valuable. As challenging as it might be to find the time, there’s no reason to make the same mistake twice when you can learn from other founders who’ve been there and done it before. I’ll never forget when, as a first-time founder, I implemented a sales commission plan that almost bankrupted my company. I crafted the plan without consulting with any veteran sales leaders and without considering how the possible scenarios could play out. I’ll never make that misstep again, but I wish I’d asked for counsel in the first place from someone who could have prevented my sloppy mistake. Our team developed the with the aim of making startup advice from accomplished leaders accessible to everyone — a playbook for how to build an early-stage startup and grow as a leader. Founder Playlist When we first embarked on this project, we were taken aback by how many founders swiftly agreed to participate. It quickly became clear how many founders were eager to share what they wish they had asked someone at the start of their own founder journeys. In total, more than 45 founders and senior leaders participated, offering 475 short audio and video clips of advice. It’s probably time to face the fact that you will never read that stack of leadership books on your shelf; you’re just too busy. Everyone is pressed for time these days and we’re increasingly wired for shorter bursts of information, so we cut straight to the essentials. Imagine your favorite podcast, but just the golden nuggets of advice you want to highlight from each segment. After listening to all the featured founders share their advice for fellow founders, three key themes stuck out to me. Building Healthy Co-Founder Relationships According to , only 25% of startups survive, often due to unhealthy co-founder dynamics. Before you rush into choosing a partner, it’s critical that you spend time thinking about your own mission and values, which complementary skills you need in a partner, and the qualities you’re seeking in a co-founder. HBS Professor, Shikhar Ghosh In the Co-Founder Relationships playlist, founders like Brian Halligan (CEO, HubSpot), discuss why having defined roles among co-founders is key to success. Halligan shares that he knew that his co-founder, Dharmesh Shah, was the one when he realized they had complementary skill sets in sales and engineering. In the same playlist, other founders discuss how they quickly learned the 50/50 equity splits with co-founders didn’t make sense, and tough lessons learned about what happens when a company doesn’t work out. Navigating Investor Meetings For many founders, one of the most stressful hurdles to surmount is raising the capital you need to get started –– crafting your story, building a target list of investors, navigating investor meetings, and negotiating term sheets. In the Fundraising playlist, Steve Kokinos (CEO, Algorand) emphasizes that it’s ok to say you don’t know the answer to a potential investor's question. In fact, it creates trust and builds confidence through transparency, as long as you follow up by refocusing the conversation on where you want it to go. In conjunction with admitting what you’re still figuring out, project how you have command of the business such as how you’ll grow, scale, understand the market, and what challenges you’re solving. Fellow Pillar Partner and former E Ink CEO, Russ Wilcox, articulated that it’s important to keep in mind how an investor is evaluating the company, including whether the opportunity fits their investment scope right now and whether you could see yourself spending a decade collaborating with the founder. Investing in Your Mental Health When you’re pouring your life into building a company, it’s essential to take time to invest in your health and mental wellness. It’s so easy to kick this item to the bottom of the to-do list when you have some many competing priorities, but the reality is that if you want to take care of your team, you have to start by taking care of yourself. It’s not an indulgence; it’s an investment in your company. Steve Conine, Co-Founder of Wayfair, shares in the Founder Playlist that when you step back with a clear perspective, even the worst-case scenario often really isn’t that bad. Steve also suggests that a durable business is one that is set up so you can take some time off; a business that is run like a sprint isn’t really sustainable in the long run. The reality is that the founder journey is incredibly hard. While it can be energizing, it can also be lonely and isolating –– you’re often on an island of one. One of the best things I can recommend to any founder is to build relationships with other founders, on your own or through a CEO group, who you can confide in and who can offer support and a sounding board. Amy Villeneuve of Amazon Robotics (Kiva Systems) articulates this best, "Founders tend to discover early that it is lonely at the top. You bear the weight of the company as soon as you hire your first employee. Having access to advice from others who have gone before you, is invaluable.” While you might feel like the only person in the world experiencing a rough patch, as soon as you start to talk to your peers, you begin to realize that you’re not alone.

The Founder Playlist: Reflections on Really Good Advice from 45 CEOs

The propagation of artificial intelligence (AI) is making a significant impact on society, changing the way how we work, live, and communicate. AI today is allowing the world to diagnose diseases and develop clinical pathways. It is also being used to match individuals’ skill sets with job openings and create smart traffic that leads to the reduction of pollution. There are many examples of applying AI technologies in the sustainable growth of the planet and organisations. It is time to solve some of the world’s biggest problems with emerging technologies such as AI. AI should work for the planet and not against it. According to the United Nations there are 17 sustainable development goals (SDGs) to transform our world: Source: About the Sustainable Development Goals Many of the 17 goals apply directly to the environment and humans’ influence over it. Are we a part of the people or organisations that influences sustainable growth? The short answer is yes. I firmly believe that exist several types of influence on sustainable growth: direct impact and indirect impact. The types of impact can be applied to one organisation and its product/solution or can be applied to a chain of organisations. Let's take a look at first example - Waze Millions and millions of people using Waze to find the best route. Maybe you did not even think about this, but while you are using Waze, you are becoming a part of the sustainable growth. Waze is not just about increasing safety, decreasing the congestion, and optimizing the traffic flow, but it also about pollution reduction. When I started thinking about the Waze and their impact, I come to the thought, that ok, if I am driving the diesel car, then Waze is navigating me to the fewer congestions roads. As a result, I will not produce much pollution, because I will avoid the traffic jam. But what if I am driving an electric car? Am I not part of sustainable growth? The answer - no, I am part of it! Again if Waze can help me avoid the traffic jam, I will drive on roads with fewer cars, so my vehicle will not be a cause of the more significant traffic jam. And this is my indirect impact on sustainable growth. I can make this thanks to Waze and AI technologies. Another example - Solar panels With the IoT sensors attached to solar plants, companies are getting the opportunity to collect the data for machine learning monitoring and prediction. Some of the benefits of applying AI technologies are remote inspection of sites, predictive maintenance, and energy resource forecasting. So the Company XYZ that is developing the machine learning models for the companies that using solar panels is making a direct impact on sustainable growth. If we will take a look deeper, we can assume that Company XYZ is using enterprise software, e.g. SAP. So SAP by providing their ERP solution to the Company XYZ is making indirect impact on overall sustainable growth, because its allowing Company XYZ to handle all the business process, e.g. accounting, sales, hr, projects and so one. Even if you are an accountant or head of human resources in the organisations that produce semi-finished products for other organisations that building the electric cars, you are also making an indirect impact on sustainable growth. Direct and indirect AI impact Based on the examples above, we can split AI solutions into two categories - those who are making a direct impact and those who are making an indirect impact. Good examples of the direct impact of the AI companies in climate change could be . They create a more effective, flexible, and autonomous grid, which will enable energy-saving and more comfortable integration of renewable energy to the grid mix. Microsoft, Agder Energi, and Powel AS AI companies with indirect impact. It is hard to measure the impact of AI companies with an indirect impact on sustainable growth. But we can defiantly say that for example, RPA solutions are making automation of the processes in any industry. By this technology allowing organizations to reduce operational costs and increase efficiency, which, of course, influences a sustainable growth chain. Also, there are a lot of companies in the AI area, using natural language processing and machine learning models to build Virtual Employees Assistants. By 2021, . predicts that 25 percent of digital workers will use a virtual employee assistant (VEA) daily. It means that AI technologies and their indirect impact will play a massive role in making people more productive & efficient. As a result, people will have more time for innovations and sustainable growth. Gartner, Inc If we understand our impact on sustainable growth and capabilities of AI technologies, we can focus on things that matter and achieve better results. Recommendations For companies Organisations, while defining their technology strategies, should take into consideration the effect that AI will have on sustainability outcomes and growth. Both types of AI solutions can have a significant impact on an organisation's efficiency. AI solutions with direct impact can provide short-term benefits, while the AI solutions with indirect impact will provide long-term benefits. For technology companies The technology companies realised their role in sustainable growth, and in parallel with creating the core products and services, they are also trying to accelerate sustainable growth. For example, AWS launched the program and millions of students can get the first steps in coding, create new solutions, get a better job. “Hour of Code,” Another example is Microsoft that started the program This program is part of Microsoft's vision in accelerating the sustainable growth, with the program you can first of all knowledge, grants, access to cloud computing, AI services, and many more. “AI for Earth.” It is the responsibility of each big corporate to start doing something in terms of sustainable growth. For Investors All types of investors should extend their portfolio with the companies that address sustainability challenges, both with direct impact and indirect impact. Such investments could speed up the transformational implications – and the commercial opportunity – of investments in technologies of sustainable growth. Regards, Andrii Rudchuk

How AI Empower Sustainable Growth of the Organisations

Powered by AI, DLT, and a global Community is a major problem in our connected world. Although misinformation and propaganda have been around for ages, ‘fake news’ is now becoming a real threat, partly due to the ease of creating, diffusing and consuming content online. What makes Fake News a hard problem to solve is the difficulty in identifying, tracking and controlling unreliable content. Even when there is early evidence for a Fake Story being circulated online, removing it or preventing people from sharing it could be perceived as an attempt of intervention and censorship. Fake news People, websites, blogs, social media are all part of the problem to some extent— intentionally or not. False or misleading stories can be easily created and diffused via the global online networks with a few clicks – in many cases silently impacting the public opinion. With the so-called ‘ ’, it is already extremely difficult to tell if what you see is true or not: latest technologies enable hacking real videos or creating artificial ones, presenting people saying things they never did – in a very realistic way. Moreover, synthesized speech matching the voice of a known person can be used to claim statements or words never said. The times when something was perceived as true just because it was ‘seen on TV’ or in a photo or in a video, are gone. deepfakes Fake News influence or even shape public opinion and (re)set the agenda. They are distributed by platforms and users - both intentionally and unintentionally. ‘Unintentional sharing’ is based on the general lack of awareness of the problem: people do not realize how often they are exposed to Fake News; they don’t know if they are influenced by misleading content; of if they are part of the problem itself by unintentionally sharing Fake News and influencing others. There are ongoing efforts within news corporations and social media companies to mitigate the problem. And some of them may prove to be somehow effective. But the fake news problem is bigger — it goes beyond the corporate boundaries. This article describes a global, immutable registry of labeled ‘fake news’ as the basis of a universal solution to the problem – on top of news organizations, social media and search engines. Utilizing technologies such as , , Natural Language processing the described platform can empower a global network of evaluators establishing continuous feedback, labeling and evaluation of a representative random sample of our global content. The objective of the system is to quantify the problem and raise global awareness by systematically taking snapshots of online content which are assessed and labeled by humans. Furthermore the platform can offer specialized APIs to expose the patterns and knowledge extracted from the on-going analysis of content in order to enable 3rd parties to predict the trustworthiness of new content – at ‘publish time’ or ‘share time’. Blockchain IPFS Fake news: Viral by design Fake content is designed to be viral; its creators want it to spread organically and rapidly. Fake stories are engineered to attract attention and trigger emotional reactions so users instantly share the ‘news’ with their social networks. With the right tricks and timing, a false story can go viral in hours. The ‘fake news industry’ takes advantage of the following ‘flaws’ or our online reality: Our online world is set up for ‘attention and instant sharing’ The performance of the global ‘news distribution network’, including social media, news corporations, opinion leaders and influencers is measured in terms of ‘attention’ and ‘user engagement’ – in many cases taking the oversimplified form of a CTR – Click Through Rate - and sharing statistics: a piece of content with high CTR will probably make it to the top of social feeds or stay more on the home page of a news site – regardless of how informative, trustworthy or useful it is. With this approach in measuring performance, content with fancy photos and ‘overpromising titles’ do extremely well – regardless of the quality of the underlying story (if there is one). Very frequently, a fancy ‘promo card’ for an article with an impressive title is enough for people to start sharing with their friends and networks – a behavior which could lead to viral effects for content with no substance – or even worse- with false information and misleading messages. Instead of the quality and trustworthiness of the content, 'expected performance' is what attracts attention and drives sharing on social media: websites and other online entities rush to reproduce stories that appear to be potentially viral; and they promote them so they get more traffic and serve more ads, to achieve their ambitious monetization goals. Content quality is rarely part of KPIs — at least not among the important ones: popular websites set goals on CTRs, page views, social sharing, and related metrics; and when there are complaints about poor content, they simply edit it or remove it. Online users tend to ‘share a lot, easily’ Another aspect of the problem is this massive group of online users who act primarily as distributors/ re-sharers of content – without having the necessary understanding or even a genuine interest in what they share. It is sad to realize that in an era characterized by instant access to world’s knowledge, the majority of the online users are ‘passive re-sharers’; they don’t create original content; they just recycle whatever appears to be trendy or likable, with little or no judgment and critical thinking. Users of this class may consume and circulate fake news — and other types of poor content — and unintentionally become part of the fake news distribution mechanism. A problem of quantification and awareness. Obviously, there are entities who intentionally drive fake news - to achieve certain political, commercial or other goals. As mentioned above, there is also a massive group of online users (acting as individuals or on behalf of companies) who unintentionally participate in the exponential spread of false stories. In fact, due to a lack of understanding and awareness, many users will probably never realize that they are part of the ‘fake news system’. Raising the global awareness around Fake News should be a key objective in every serious attempt to tackle the problem: instead of silently removing fake stories when identified and deactivating fake social media accounts, we must systematically measure the circulation of fake news across the globe, and the degree of unintentional participation of media sites and online users. We need to understand the patterns and share the knowledge we get by continuously analyzing a representative sample of world’s digital content: a global registry of enriched content, analyzed and labeled by both humans and intelligent AI agents; a global community powered by Artificial Intelligence on top of an immutable, unified content store. A platform powered by genuine human collaboration spirit assisted by our most advanced intelligent technological. The solution: A global registry of labelled Fake News The proposed ‘ ’ takes a different approach – it focuses less on the real-time classification of new content and more on a retroactive, large-scale ‘fake news’ analysis with the intent to quantify the problem, extract patterns, and share the derived knowledge. It emphasizes on measuring the level of responsibility of each of the involved parties with the objective to educate, raise global awareness and influence the Corporate Social Responsibility strategies of online corporations. Fake News Evaluation Network Imagine a ‘content sampling’ process running on a daily basis — sampling the global content publishing and sharing activity. Powered by special crawlers, this process ‘listens’ for stories and ‘news’ across a representative set of major websites, social media, and popular blogs. It discovers and organizes ‘fresh content’ and ‘new content references’ into a unified, deduplicated and immutable content store – specially designed to handle stories, facts, and their associations. Newly identified content is unified and linked to its master copy’, related ‘stories’ and relevant factual information. It is then compared against the already labeled content, with the objective to estimate the ‘degree of deviation from reality’ using ‘fact-checked versions of the same story’ and known patterns. adds significant value by identifying the story in the content (the elements of a story such as the named entities, the events, the occasion, the timeline, etc.) and matching the variations found in a large pool of noisy content of various sources and levels of quality. It then creates lists of stories that need to be evaluated and simplifies the assessment process through intelligent suggestions and recommendations (specifically what needs to be checked within each story). The global community of professionals and ‘active digital citizens’ discovers, evaluates and votes for/against certain aspects of the story – with proper justification, inline references, and annotations. Artificial Intelligence As soon as a story gets enough votes and factual checks, AI generalizes the findings to all known variations of the story and different types of coverage – allowing quantification of the reliability of both the core story and its different instances. AI components pick the patterns and keep monitoring each core story for new facts and events that need to be checked. All these as part of the immutable content store – labeled content, assessments, publisher scores, and metadata permanently stored as part of a global history – no deletions, no ‘phantom’ fake news. , and other entities consume the APIs of this platform to self-assess their compliance and progress towards a ‘better content for the world’ mission. As content is being evaluated in terms of trustworthiness, the reliability of those who produce it, promote it or distribute it is also affected: a ‘publisher evaluation system’ quantifies how website A or social media B or news corporation C is part of the global fake news problem. Having this information, media entities can take action, learn and measure the level of their responsibility in spreading fake stories. They can let their users know that certain stories they have shared, proved to be false and misleading. They can help the global effort by educating their users and demonstrating real social responsibility and meaningful actions towards a better-informed society. Social media, news corporations, blogs Companies could also integrate special APIs in order to cross-check content at ‘share time’ and notify their users if the content is already flagged or there are signals for limited trustworthiness (while leaving the sharing decision to the user). Social media could notify users who have already engaged with ‘verified fake news’ stories (liked, shared, saved, commented on, or simply consumed) and explain how to avoid such content in the future. There are countless interesting use cases — including measurements of additional aspects of content quality, global trend analysis and articulation of the dynamics of the phenomenon. This could be based on a unified content on top of or — an immutable system hosting samples of the world’s content, unified, labeled and scored in terms of trustworthiness and other qualities of digital content. IPFS Swarm Comments and thoughts are welcome.
 Based on an idea posted on https://ideacha.in References Fake News - How Blockchain and IPFS can help Democracy https://en.wikipedia.org/wiki/1%25_rule_(Internet_culture) https://en.wikipedia.org/wiki/Deepfake https://www.youtube.com/watch?v=gLoI9hAX9dw https://www.wired.com/2017/03/google-and-facebook-cant-just-make-fake-news-disappear/ Imagery: https://pixabay.com/vectors/george-orwell-eric-blair-1984-3176732/ https://pixabay.com/vectors/fake-news-propaganda-deceit-3801637/

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