Startup Stash - Go Beige, Be Bland, Take Food Photos 🍳

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The Good Thing About Food Photos

Humans are terrible at estimating the portion size of a plate of food. 

Which is why, Wade Norris and Scott Baron joined forces to establish SnapCalorie, a pioneering startup focused on promoting health. The app counts calories and analyzes macronutrients in our meals by simply snapping a photo of it.

SnapCalorie secured a remarkable $2 million in funding from some prestigious investors this month. 

Now, let's address the elephant in the room: SnapCalorie isn't the first of its kind to utilize computer vision for calorie counting. Competitors such as Calorie Mama, Lose It, Foodadvisor, and Bite.AI have all made attempts at achieving this feat, albeit with varying degrees of success.

So what’s different about SnapCalorie? 

The app utilizes depth sensors to accurately measure portion sizes, providing a distinct advantage. Additionally, it incorporates a team of human reviewers to ensure precise results. But that's not all. The company's algorithm supposedly surpasses human capability in estimating calorie content. This algorithm - based on a unique dataset of 5,000 meticulously curated meals - identifies the different types of food present in a photo and accurately measures the portion size of each item.

At this point, it’s crucial to acknowledge the skepticism prevailing within the health industry, and rightly so. A study conducted in 2020 compared several prominent AI-based calorie counters and found that the most accurate among them, Calorie Mama, only achieved a 63% success rate.



Everyone's Going Beige

Light a candle, wear pyjamas, go to bed early.

On Instagram and TikTok, a peculiar trend has emerged among the younger generation (under 30) - an ideal life that is surprisingly monotonous and centered around repetitive daily routines. 

Perfect existence = mundane activities

The key to living your best life seems to lie in donning matching pajamas, cooking at home, exercising, and sleeping early. Videos showcasing bedtime rituals, visits to coffee shops, or ways to romanticize your life have inundated our social media feeds.

Reasons: Within tightly structured lives and economic uncertainties, individuals yearn for the elusive sense of security. The constant noise of social media also amplifies the appeal of quieter, more predictable lives.

Case in point: Earlier this month, a viral video on Twitter showed a typical workday of a 28-year-old man, featuring by a visit to the gym, heating a meal at home, and playing with his dog. The video caption called this a “depressing lifestyle”. People swiftly criticized this, pointing out that having a home, a stable 9-to-5, a gym membership, and a pet are desirable aspects of life, especially when so much of our existence is plagued by chaos.

Naturally, influencers of the mundane life, aka beige-fluencers, have been making immense profits from this trend, selling linen trousers and enticing followers to spend exorbitant amounts on wellness retreats

We are led to believe that we are being empowered, but in reality, we're being persuaded to buy cream-colored office attire and sweatpants.



Forget What You've Learned

Google has introduced a machine "unlearning" competition to address the issue of sensitive data in AI systems and comply with global data regulations. Machine learning is widely used to predict outcomes and answer complex questions based on its training. However, Google aims to implement selective amnesia in its AI algorithms through machine unlearning, removing specific datasets without impacting performance. 

Reason: In today's digital era, machine learning projects face various challenges, including cybercriminals misusing data for bullying, blackmail, data poisoning, denying online access, deceiving face recognition, and generating deepfakes.

Google believes that teaching algorithms to forget previously learned data will give individuals more control over their sensitive information. This approach would simplify compliance with GDPR guidelines, allowing companies to serve users who request their data to be forgotten.

Machine unlearning enables people to remove their data from algorithms, preventing others from benefiting from it, and safeguarding themselves from AI-related risks.



Shorts ⏳
🪧 Strike Resort - The biggest hospitality strike in US history kicked off in yesterday when about 15,000 hotel workers walked off their jobs.

🍎 Historic Value - Apple shares closed at $194 on Friday making it the first company in history to close above a $3 trillion valuation. 

👟 Missing From Work - An Italian teacher was sacked for being absent from work for 20 years. She is planning to sue the school. 

☢️ Radioactive Roads - Florida has decided to allow radioactive waste in road construction.

Twitter Limits - Musk slapped daily limits on the number of posts users can see each day: 1,000 for unverified users and 10,000 for paying verified users.

🍲 A Tasty List - An interesting list of 150 of the world's most legendary restaurants, complete with an the iconic dish from each one.


Stash Recommends: Tools to Explore
🏋️‍♀️ PayFit: An integrated payroll and HR management platform tailored to startups and SMEs.

💼 WerckerA docker-based continuous delivery platform that helps developers build and deploy applications.

🧭 Pivotal Tracker: The agile project management tool of choice for developers around the world for real-time collaboration around a shared, prioritized backlog.
 
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