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Materials scientist and beauty icon, Dr Eric Pressly, was just 30 when he helped to create the world’s most famous hair-bonding product, Olaplex. Now he’s started his own brand, epres Hair Care, and it’s set to disrupt the multi-billion care industry.

Hair products were never part of the career plan for materials scientist, Dr Eric Pressly. He was interested in starting a pharmaceutical company after finishing his PhD and working on clinical trials. But a sliding doors moment in 2012 changed his career trajectory when he was approached by the founders of Olaplex, Dean and Darcy Christal to create a new hair care product.

Working tirelessly in his surfboard-littered garage in Santa Barbara, California,  Dr Pressly developed a bond-building formula that would change the game. Today the products, used by the likes of Drew Barrymore and Kim Kardashian, are used in almost every leading hair salon in the world.

Pressly’s creation, a hair-bonding repair solution, is used by many leading hair salons around the world and is readily available as a “take home” solution from most major hair product retailers. Olaplex is now valued at around $US14 billion. Dr Pressly, himself, has more than 100 patents in bond-repair technology.

A new direction, improved technology

When Pressly finally left Olaplex he wasn’t sure if he would stay in the hair product industry, he told Forbes Australia. As the father of a new baby son, he wanted to focus on his growing family, travel and the career of his wife, a singer-songwriter.

However, the pull of science and improving formulations eventually got the better of Dr Pressly, and he began working on improving his repair-bonding technology once again. He wanted the formula to not only repair hair damage, but reverse it altogether.

“I knew I had the better technology. So I focused on making it easier, simpler, more reliable and better for the planet than everything [I had created] in the past.

Dr Pressly’s plans to travel with his wife, a singer-songwriter, and new baby were derailed because of COVID, so he went back to the drawing board, creating new hair formulations that rivalled his previous inventions.

“What I really enjoy about the cosmetic space is the ease of getting into the market versus pharmaceuticals.”

He was approached by the now co-CEO of Epres, Michael Sampson – who has worked in leadership positions for a number of huge names in beauty, such as L’Oreal – to develop some new hair technology. At the time, Dr Pressly had just started his family and had admits had “got used to the simple life”.

“I knew if I hit the go button, is it going to be like this…busy! I was thinking about whether or not I wanted to do that. But the technology was too good not to.”  

Unlike its main competitors that can take hours in the salon chair to work, Dr Pressly says epres TM has been designed to be a simple one-step solution that works within 10 minutes. He says it has also been developed with the environment in mind – containing only four vegan, biodegradable ingredients.  He says the product was created for “performance first” – it needs to work “or people won’t use it again” – but it also needed to be quick to use and sustainable.

In February this year (long after Dr Pressly left the company), Olaplex was sued by 28 women who claim its products caused hair loss, blisters and other conditions. The company said in a statement on Instagram that its products “do not cause hair loss”. “We are prepared to vigorously defend our Company, our brand, and our products against these baseless accusations,” it said on the social media platform.

“epres TM is a testament to our commitment to balanced science and exceptional results and I consider it my best invention yet,” Dr Pressly said. “It’s the culmination of years of research and development, addressing various hair damage issues in a single step.

Look back on the week that was with hand-picked articles from Australia and around the world. Sign up to the Forbes Australia newsletter here or become a member here.

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At&T Pulls Bid For T

We had an inclination that it was coming, especially when the AT&T and T-Mobile merger was withdrawn from the FCC, but AT&T just confirmed in a press release that it agreed to kill the $39 billion purchase of T-Mobile USA announced in March. The result of the decision is AT&T both paying the agreed to $4 billion pretax charge by Q4 2011, as well as entering “a mutually beneficial roaming agreement with Deutsche Telekom”.

AT&T chairperson and CEO Randall Stephenson said this, regarding the issue:

AT&T will continue to be aggressive in leading the mobile Internet revolution. Over the past four years we have invested more in our networks than any other U.S. company…To meet the needs of our customers, we will continue to invest. However, adding capacity to meet these needs will require policymakers to do two things. First, in the near term, they should allow the free markets to work so that additional spectrum is available to meet the immediate needs of the U.S. wireless industry, including expeditiously approving our acquisition of unused Qualcomm spectrum currently pending before the FCC. Second, policymakers should enact legislation to meet our nation’s longer-term spectrum needs.

The full press-release from Stephenson is shown below.

DALLAS–(BUSINESS WIRE)–AT&T Inc. (NYSE: T) said today that after a thorough review of options it has agreed with Deutsche Telekom AG to end its bid to acquire T-Mobile USA, which began in March of this year.

“To meet the needs of our customers, we will continue to invest”

The actions by the Federal Communications Commission and the Department of Justice to block this transaction do not change the realities of the U.S. wireless industry. It is one of the most fiercely competitive industries in the world, with a mounting need for more spectrum that has not diminished and must be addressed immediately. The AT&T and T-Mobile USA combination would have offered an interim solution to this spectrum shortage. In the absence of such steps, customers will be harmed and needed investment will be stifled.

“AT&T will continue to be aggressive in leading the mobile Internet revolution,” said Randall Stephenson, AT&T chairman and CEO. “Over the past four years we have invested more in our networks than any other U.S. company. As a result, today we deliver best-in-class mobile broadband speeds – connecting smartphones, tablets and emerging devices at a record pace – and we are well under way with our nationwide 4G LTE deployment.

“To meet the needs of our customers, we will continue to invest,” Stephenson said. “However, adding capacity to meet these needs will require policymakers to do two things. First, in the near term, they should allow the free markets to work so that additional spectrum is available to meet the immediate needs of the U.S. wireless industry, including expeditiously approving our acquisition of unused Qualcomm spectrum currently pending before the FCC. Second, policymakers should enact legislation to meet our nation’s longer-term spectrum needs.

“The mobile Internet is a dynamic industry that can be a critical driver in restoring American economic growth and job creation, but only if companies are allowed to react quickly to customer needs and market forces,” Stephenson said.

To reflect the break-up considerations due Deutsche Telekom, AT&T will recognize a pretax accounting charge of $4 billion in the 4th quarter of 2011. Additionally, AT&T will enter a mutually beneficial roaming agreement with Deutsche Telekom.

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Data Scientist’s Insights: Strategies For Innovation And Leadership

Introduction

Welcome back to the success story interview series with a successful data scientist and our DataHour Speaker, Vidhya Chandrasekaran! In today’s data-driven world, data scientists play a crucial role in helping businesses make informed decisions by analyzing and interpreting data. With their expertise in statistics, machine learning, AI, and programming, they are able to extract meaningful insights from complex datasets.

Interview Excerpts with Vidhya Chandrasekaran AV: Hello Vidhya! Please introduce yourself and give us an insight into your professional and educational background.

Vidhya: Hi, I work as a senior manager at PayPal and lead ML and AI product management. I have about 18 years of experience in data and 8 years in leadership. With Bachelor’s in Mathematics and a Masters in Computer applications, I also did a 1 year PG program in AI with Great Lakes. Currently, I am doing my Doctoral research program on Personalization with Data.

At PayPal, over the past 5 years, I have had the opportunity to lead and build BigData, ML Engineering, AI product, and ML Science teams and initiatives. In my current role, I show the ML for Merchant products and Marketing, building Product recommendations and personalization solutions.

AV: That sounds spectacular and insightful. You started as a Software Engineer; how did you get into the field of Data Science? AV: I agree. A great mentor can help you climb the corporate ladder easily, which shows in your career trajectory. How do you foster a culture of innovation as a leader in Applied Data Science?

Vidhya: Unlike research teams, Applied ML teams operate under tight guidelines and strict timelines. Due to these constraints, they sometimes do not have the same luxury to explore new technologies, algorithms and implement new papers. However, I have remained conscious of the importance of innovation in ML teams, where every single day, a copious amount of new things going on.

Here are some of the strategies that have been instrumental in my management of an applied ML team without compromising on long-term innovation.

Providing 10 to 15% of the time for working on stretch assignments or research/Proof of concepts.

Encourage the culture of intra and inter-team collaboration with an emphasis on feedback loops – Innovation happens more in groups than in isolation.

Allow safe space to fail. Machine learning is experimentation compared to software engineering and has many possibilities of failing. If failing safely is not allowed, the attempt to innovate is curtailed.

Make innovation a part of the goals.

AV: Those are some pretty interesting strategies you follow. That’s great! Although, managing a team can be difficult. What do you consider a top challenge in leading a Machine learning and Artificial Intelligence team?

Vidhya: One of the challenges is striking a fine balance between timely business deliveries and innovation which is a time-intensive process. Apart from the fact that innovation is non-negotiable in any Tech Industry, also as a leader, we are responsible for our team’s careers by providing them opportunities for continuous learning and keeping them motivated, especially in AI and Data Science where the related tech is constantly moving at a faster pace.

AV: What do you consider is key to succeeding in the Applied AI team?

Vidhya: Most projects fail due to poor planning. AI Product managers play a key role in this phase. The key first step is understanding the business problem and where AI can solve it. As part of the planning, estimating opportunity sizing and agreeing upon clear, well-defined KPIs is of tantamount importance. A key next step is working backward from the expected outcome to arrive at and crystalize the appropriate metric or KPI. For example, the model could bring more customers to the website or drive new customer acquisition. Model metrics like Precision, Recall, or F1 are often misunderstood as KPI; the business would not worry about the model metrics but would be very much interested in the business metrics.

Developing capabilities and processes to bring an idea to fruition is another crucial aspect of success. Incorporating capabilities such as data catalog search functionalities, retraining automation, monitoring capabilities, continuous integration, etc., can significantly shorten the time required to test and learn from your ideas. This approach also guarantees that the valuable resources of our teams are not diverted towards monotonous and repetitive tasks but instead utilized to create engaging solutions.

Try At Least One New Thing in Every Model Development. The ‘newness’ can be anything like a new algorithm, a new type of data that is experimented or different feature engineering techniques.

Fail Fast: Try to get the model deployment as soon as possible. Going for a perfect model, excellent results, and a new in-the-market algorithm could be enticing but oftentimes comes with an opportunity cost. Try a simpler, lean model to measure success or fail fast as soon as possible. We can always go for improvisation later. Shooting for a faster time to market and incrementally improving it to a cutting-edge model is critical.

AV: According to your profile, you have teaching experience as a mentor; how do you think that your experience as a mentor has influenced your career growth and success in machine learning?

Vidhya: Teaching is a great way to learn. I signed up to teach AI/ML on the weekend when I was doing my PG program in AI. When you teach a topic to someone else, you have to organize your thoughts, break down complex concepts into simpler ones, and explain them clearly and concisely.

I have also learned from mentoring e-commerce business leaders on Data driving marketing. As part of the Chennai Entrepreneurial chapter’s mentorship program. This gave me a perspective on strategic/ structural thinking, decision-making, planning and also made me come out of my comfort zone.

Vidhya: I followed a disciplined learning approach for many years, spending either regular hours in the week or on the weekends learning from courses, blogs, and books. These days, though I continue my individual learning, I spend lesser time than before as I learn from my team directly when they try novel things; that is a perk of working with a team who are way smarter than you.

The latest development that I am very excited about, like several others, is what is happening with Generative AI, which seems to have all ingredients to disrupt everything from the creative industry to personalization. This is set to revolutionize the way businesses are done. As more concerns are raised regarding ethics and the possibility of obfuscated narratives, I am curious to see how Governments, organizations, and policymakers create processes to fortify the social fabric against potential threats.

Vidhya: Although there is no one-size-fits-all approach, I believe that the strategies and plans for transitioning to a data science or ML role are dependent on an individual’s career stage.  Transitioning from a junior role is significantly simpler than a mid-management or a senior-level role.  Those that are individual contributors can start their learning from basics, learning statistics, probability, Mathematics, and basic ML concepts.  There are several free courses and YouTube resources. Following a bottom-up approach is important when learning, as it is easy to get a model done in a few lines of library code. This knowledge is not sustainable.   There are several hackathons that one can compete to learn or just follow along the code to understand different feature engineering and model strategies. Once you have gained sufficient expertise on the concepts, plan to switch over to a team internally that has exposure to ML projects.

While it is crucial for individuals in senior and middle management positions to comprehend the capabilities of machine learning, it is even more critical to acquire expertise in the broader context of artificial intelligence strategy, engineering, and integration requirements. They can start to identify opportunities to innovate in their own area/project or domain and then communicate the success to their leadership and stakeholders. They can use their small initial successes to build ML capabilities and teams internally.

Some Resources for learning ML ground up – ML and Deep learning specializations by Andrew NG in coursera:

Medium and Analytics Vidhya blogs

Kaggle Kernels

Conclusion

In this interview, Vidhya Chandrasekaran’s journey showcases the transformative impact of data science in the technology industry. Her insights, challenges, and strategies for fostering innovation offer valuable lessons for aspiring data scientists and leaders in applied data science.

Related

Dogecoin Going To Moon! Four Billion Doge Traded In 24

Dogecoin (DOGE) presented a unique proposal unlike seen when it launched.

Dogecoin (DOGE) started in 2013, coming into the crypto industry when it was still in its infancy. For many crypto users, blockchains weren’t meant to be named after a meme and certainly not for “joke” purposes. This attracted holders in their hoards to see what the meme coin could do, but also a lot of skepticism about the volatility DOGE presented. However, curiosity won over, and for a token that wasn’t created to have any real-world utility, it recorded an unexpected height- though below the dollar- in 2023. WhaleStats’ analysis of the top 100 Dogecoin holders on the Binance Smart Chain (BSC) indicates a whopping 414% rise in trading volumes as well as a 10% increase in active addresses. This follows as Dogecoin returns among the top 10 purchased tokens for the 100 biggest BSC whales in the last 24 hours. Notably, large transactions, which typically refer to those above $100,000 on the Dogecoin network, were up 17% in the last 24 hours, per IntoTheBlock data. Dogecoin (DOGE) presented a unique proposal unlike seen when it launched. There wasn’t any public sale to boost the coin’s worth. Instead, they set a cap of 100 billion coins and told anyone with average computing power to begin mining Doge immediately. It also had a random block reward system until things were fixed to give miners fair chances of earning more.

Dogecoin (DOGE) started in 2013, coming into the crypto industry when it was still in its infancy. For many crypto users, blockchains weren’t meant to be named after a meme and certainly not for “joke” purposes. This attracted holders in their hoards to see what the meme coin could do, but also a lot of skepticism about the volatility DOGE presented. However, curiosity won over, and for a token that wasn’t created to have any real-world utility, it recorded an unexpected height- though below the dollar- in 2023. WhaleStats’ analysis of the top 100 Dogecoin holders on the Binance Smart Chain (BSC) indicates a whopping 414% rise in trading volumes as well as a 10% increase in active addresses. This follows as Dogecoin returns among the top 10 purchased tokens for the 100 biggest BSC whales in the last 24 hours. Notably, large transactions, which typically refer to those above $100,000 on the Dogecoin network, were up 17% in the last 24 hours, per IntoTheBlock data. Dogecoin (DOGE) presented a unique proposal unlike seen when it launched. There wasn’t any public sale to boost the coin’s worth. Instead, they set a cap of 100 billion coins and told anyone with average computing power to begin mining Doge immediately. It also had a random block reward system until things were fixed to give miners fair chances of earning more. A renowned crypto trader and analyst, anonymously known as Smart Contracter, believes that dogecoin (DOGE) is all set for a massive bull run. The trader informed his Twitter fanbase of 210,500 that DOGE might be headed towards an enormous bull run, after experiencing a bearish market for several months.

Analysis: Qualcomm Just Spent $1.4 Billion To Compete With Apple’S Arm Laptops

What is Nuvia and what does it do?

Why buy Nuvia now?

Gary Sims / Android Authority

In a nutshell, Qualcomm is after Nuvia’s custom Arm design expertise. The logical starting place will be in the data center market, where Nuvia is already designing chips. Arm-based CPUs are gaining steam in the cloud computing space, with Amazon’s Graviton Arm Neoverse looking to shake up the market. This deal will therefore have caught the attention of Intel and AMD. Qualcomm has already made it clear that it plans to leverage Nuvia’s custom design approach to cover swathes of its chipset portfolio too.

5G, the convergence of computing and mobile architectures, and the expansion of mobile technologies into other industries are significant opportunities for Qualcomm.

Cristiano Amon, President and CEO-Elect, Qualcomm Incorporated

Qualcomm’s press release makes heavy mention of combining Nuvia CPUs alongside its in-house GPU, DSP, AI, and multimedia accelerators, for comprehensive platforms for a variety of markets. Smartphones, driver assistance systems, extended reality, networking, and next-generation laptops are all on the list. It’s that latter option that could turn out to be the driving factor behind the whole deal. That’s because it would provide Qualcomm with the technology to compete with Intel, AMD, and now Apple in the consumer PC space.

Qualcomm’s more recent Kryo CPUs now use off-the-shelf Cortex-A CPUs designed by Arm. This approach has worked well for smartphone processors. Cortex-A performance has proven more than good enough, leaving Qualcomm to focus on in-house GPU, DSP, ISP, and other components that play a key part in its heterogeneous approach to mobile computing.

It’s exciting to see NUVIA join the Qualcomm team … moving forward, we have an incredible opportunity to empower our customers across the Windows ecosystem.

Panos Panay, Chief Product Officer, Microsoft.

Qualcomm is assisting Microsoft with its own support for Arm-powered PCs, providing Snapdragon platforms for the Windows on Arm initiative. Current-gen performance is fine for portable home and business laptops but is underwhelming for more demanding creative applications and enterprise solutions. If the two companies share the vision for a single Arm architecture spanning mobile, PC, and server products, Qualcomm will require even more performance than Arm’s Cortex-A CPUs have offered thus far. The solution appears to be to take a leaf from Apple’s book and go down the custom architecture route.

Returning to at least some level of custom CPU design affords Qualcomm greater control over its destiny.

It’s possible that the direction of Arm’s Cortex-A roadmap may change under NVIDIA’s influence and may not align with Qualcomm’s ambitions or needs. Access to or pricing of Arm’s portfolio could also change, with NVIDIA retaining the highest performing part for internal use only. Or the business model may stay the same.

Returning to at least some level of custom CPU design affords Qualcomm greater control over its destiny. Building up an in-house design team would also be an invaluable asset in the unlikely event that Qualcomm wants to transition from Arm to an entirely new instruction set in the future. This is a sensible plan when one of your biggest competitors is set to control an essential business partner. At the same time, Arm may not be too happy at potentially losing out on-chip royalties from one of its biggest customers.

At&T Agrees To Purchase Mexican Carrier Iusacell For $2.5 Billion

“Mexico is still in the early stages of mobile Internet capabilities and adoption, but customer demand for it is growing rapidly. Iusacell gives us a unique opportunity to create the first-ever North American Mobile Service area covering over 400 million consumers and businesses in Mexico and the United States.” – AT&T CEO Randall Stephenson

AT&T to Acquire Mexico Wireless Provider Iusacell

AT&T* (NYSE:T) has entered into an agreement with Grupo Salinas to acquire Mexican wireless company Iusacell for US$2.5 billion, inclusive of Iusacell debt. Under the terms of the agreement, AT&T will acquire all of Iusacell’s wireless properties, including licenses, network assets, retail stores and approximately 8.6 million subscribers. The acquisition will occur after Grupo Salinas, the current owner of 50 percent of Iusacell, closes its announced purchase of the other 50 percent of Iusacell that Grupo Salinas does not own today.

Iusacell offers wireless service under both the Iusacell and Unefón brand names with a network that today covers about 70 percent of Mexico’s approximately 120 million people. AT&T plans to expand Iusacell’s network to cover millions of additional consumers and businesses in Mexico.

“Our acquisition of Iusacell is a direct result of the reforms put in place by President Peña Nieto to encourage more competition and more investment in Mexico. Those reforms together with the country’s strong economic outlook, growing population and growing middle class make Mexico an attractive place to invest,” said Randall Stephenson, AT&T chairman and CEO. “Iusacell gives us a unique opportunity to create the first-ever North American Mobile Service area covering over 400 million consumers and businesses in Mexico and the United States. It won’t matter which country you’re in or which country you’re calling – it will all be one network, one customer experience.

Creating first-ever North American Mobile Service area to cover 400 million Mexico & U.S. consumers, businesses

Mexican regulatory reforms, growing population, growing middle class & growing economy make investment attractive

Iusacell serves approximately 8.6 million subscribers; network today covers 70% of Mexico’s population; AT&T to expand network to millions more

Early stages of mobile Internet adoption; OPPOrtunity to bring world-class mobile Internet speeds & quality to Mexico

Separately, AT&T says Project VIP ahead of schedule — expects 2024 Cap-Ex in $18 billion range

The transaction is subject to review by Mexico’s telecom regulator IFT (Instituto Federal de Telecomunicaciones) and Mexico’s National Foreign Investments Commission. AT&T expects the transaction to close in the first quarter of 2024.

Separate from its acquisition of Iusacell, AT&T said its Project VIP network investment plan is ahead of schedule. AT&T has essentially completed the expansion of its 4G LTE network, which now covers more than 300 million people in the United States. It has completed the build-out of wired high-speed Internet service to 57 million U.S. customer locations. And the company has deployed fiber connections to 600,000 of its planned 1 million multi-tenant U.S. business locations.

AT&T’s VIP-related capital investment levels will peak in 2014, as the company has said previously. As a result, AT&T expects its 2024 capital expenditure budget for its existing businesses to be in the $18 billion range. This will bring the company’s capital spending as a percent of total revenues to the mid-teens level — consistent with its historical capital spending levels.

AT&T’s 2024 capex guidance does not affect the company’s commitment, when it closes its acquisition of DIRECTV, to begin enhancing and expanding its U.S. broadband network to 15 million customer locations, primarily in rural areas.

AT&T will provide guidance on the pro-forma financial impacts of its DIRECTV and Iusacell acquisitions when those deals close. Upon completion of both deals, AT&T’s revenues will be more diversified across services and geographies.

AT&T said it will continue to focus its capital investments on the most strategically important assets and opportunities, such as acquiring DIRECTV and Iusacell, while continuously reviewing and rationalizing its portfolio of less strategic assets.

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