$AKAM

While everyone is focused on the obvious AI winners, some of the most interesting charts are developing quietly in the background.

Akamai has now:

• reclaimed its long-term trend
• broken above the 200-week moving average
• built a strong higher-low structure
• attracted steadily increasing volume
This isn't a hype story.
It's infrastructure.
The AI boom needs compute.
Compute needs networks.
Networks need delivery and security.

That's where Akamai sits.

One of the most overlooked charts in technology right now.

Since next week at Computex in Taiwan will be Microsoft/NVIDIA/Arm + Qualcomm’s big week, don’t forget AMD + Intel…

🧠 Localmaxxers, the local AI silicon race is getting wild 👇

✅ AMD Halo
Strix Halo is here. Gorgon Halo / Ryzen AI Max PRO 400 is official → up to 192GB unified memory + 160GB VRAM (end of '26 w/AMD Agent PC)

🟡 NVIDIA N1X
Expected Windows-on-Arm debut with Microsoft. Still not officially announced. Official NEXT WEEK!!

🧪 Intel Razor Lake-AX
Rumored Halo-class APU → on-package memory, maybe LPDDR6, plus a much bigger Arc iGPU. end-'28

🐍 Intel Serpent Lake
Rumored Intel x86 + NVIDIA RTX tile SoC → official Intel/NVIDIA RTX SoC partnership exists, but “Serpent Lake” name/specs/timing are still leaky. Rumored late ’28/’29.

🔮 AMD Medusa Halo
Rumored Zen 6 + RDNA 5 + LPDDR6 follow-up. Rumored late ’27/’28.

💪Localmaxxing is becoming the new laptop war.

With all the Microsoft-Nvidia-Windows-Arm N1X conversations next week, Intel's Panther Lake will have its work cut out for it in the battle for Local AI.

Intel on paper beats AMD. With up to 180 TOPS of total AI performance, it significantly outperforms AMD’s Ryzen AI 400 series (~120–130 TOPS).

Here are some advantages:
⚡ 35–47% faster local LLM inference in real-world tests
🎮 Much stronger Xe3 Arc GPU for running larger models locally
🔋 Better balance of performance + efficiency than previous Intel chips
🤖 Excellent for agentic AI, coding, and multimodal tasks

Panther Lake is currently one of the strongest platforms for local AI on laptops. 🔥 Waiting to see how N1X compares.

$FIVN

Everyone talks about AI chips.

Far fewer people talk about where AI actually gets deployed.

Customer service.
Contact centers.
Enterprise automation.
AI agents.
That's where Five9 sits.
Now look at the chart:
• multi-month trend reversal
• higher lows developing
• volume expanding
• momentum improving
• reclaiming key moving averages

The strongest trends often begin long before they become popular.

This is one of the more interesting software charts on my screen right now.

$MLGO

One chart that keeps showing up on my radar.

After months of compression, the stock is now pressing directly against a major descending trendline.

What stands out:

• volatility contraction
• improving structure
• volume starting to return
• reclaiming key moving averages
• breakout attempt developing
The move hasn't happened yet.
But that's usually when the best risk/reward opportunities appear.
Worth watching closely next week.

$FJET One chart quietly getting stronger while nobody is paying attention.

After months of consolidation, FJET is now pressing directly against a major descending trendline.

What stands out:

• higher lows forming
• volume returning
• volatility compression
• improving momentum
• aerospace and space themes are hot

The move hasn't happened yet.
But the best setups usually look boring right before they become obvious.
Worth watching very closely next week.

$KITT One of the most compressed charts on my screen right now.

After weeks of consolidation, KITT is now pressing directly against a tightening triangle structure.

What stands out:

• sellers disappearing
• volatility compression
• higher lows forming
• volume drying up
• defense and robotics themes gaining attention
The biggest moves often start when nobody is paying attention.
This chart looks very close to a decision point.
Worth watching closely next week.

SoftBank just pledged €75B to build Europe’s largest AI computing facility in France, turning cheap, stable nuclear-heavy power into the raw fuel for training and running bigger AI systems.

The plan starts with €45B for 3.1GW of capacity in Hauts-de-France by 2031, then adds another 2GW, creating a 5GW AI complex roughly comparable to the power draw of a major city.

Dunkirk is the anchor site, with Schneider Electric expected to help build an AI infrastructure and robotics manufacturing hub around the project.

The weak point is financing, because industry estimates put 1GW of AI infrastructure near $50B, meaning SoftBank will probably need heavy project debt and outside partners.

ByteDance is building its own AI data-center CPUs because running agents at TikTok scale now depends on scarce server processors, not only Nvidia GPUs.

inspired by Groq's "language processing units," they are testing both Arm and RISC-V, which lets it compare a mature commercial design against a more controllable open instruction set before mass production.

The market is seeing a 10%-35% quarterly CPU price increases and long supply delays, hence making an in-house silicon is now cost and supply-chain move, not just a prestige project.

So ByteDance wants to both reduce dependence on restricted foreign AI hardware and make inference cheaper per query.

The deeper shift is that AI agents is now turning CPUs into strategic chips. A
gentic inference stresses CPUs much more because one user request can trigger many smaller steps: retrieve files, call a tool, query a database, run a model, check the answer, call another model, send data across servers, and manage memory.

However, ByteDance does not seem to have in-house chip design teams and is reportedly relying on several external partners, who are also expected to handle the actual silicon manufacturing.

🇮🇷 Every single stock on the Tehran Stock Exchange closed green today. Not one in the red.

First time in the exchange's history.

Iran's market is pricing in the deal before the ink exists. When a population that's been cut off from the internet for 5 months sees every stock go green on the same day, they know something is coming.

The Supreme Leader hasn't signed. The terms are still disputed. The market already decided.

Source: Middle East Spectator

$META is building the AI wearable stack from every angle, pendant, glasses, enterprise subscriptions, and a dedicated “Wearables for Work” service.
It’s a software monetization play disguised as hardware. Meta AI Assistant, Hatch, and whatever comes next, all tied to recurring revenue on your face, this is like Nvidia’s CUDA.

Apple is coming. Google never left. The wearable OS wars are starting

WEEKLY PERSPECTIVE

We pushed to new highs again this week in the space sector. Here's where we are on year-to-date returns.

$SATL 385%
$MNTS 194%
$SPIR 192%
$RDW 172%
$PL 151%
$LUNR 145%
$BKSY 133%
$VSAT 114%
$FLY 96%
$RKLB 89%
$SPCE 88%
$VOYG 78%
$MDA 45%
$VELO 45%
$ASTS 36%
$AMPG 35%
$SIDU 13%
$YSS -3%
$HAWK -3%

Which one is your top pick for the rest of the year?

36 Strongest Industry Groups At 1-Month RS (Sorted)

$ICLN — Clean Energy
$TAN — Solar
$BUZZ — Social Media
$DRAM — Memory
$ARKG — ARK Genomics
$AIQ — AI Software & Data Processing
$XSW — Software (Equal Weight)
$IGV — US Tech / Software
$JETS — Airlines
$BLOK — Blockchain
$ARGT — Argentinian Equities
$CIBR — Cybersecurity
$FDN — US Internet Giants
$ARKW — ARK Internet & Next-Gen Tech
$WCLD — Cloud Tech
$IDGT — Digital Infrastructure & Data Centers
$CLOU — Cloud Infrastructure & SaaS
$ARKX — Space Exploration
$XAR — Aerospace & Defense (Equal Weight)
$ARKQ — ARK Robotics & Automation
$ITA — Aerospace & Defense
$XTN — Trucking
$EWY — South Korea Equities
$QTUM — Quantum Computing / AI
$UNG — Natural Gas
$WGMI — Crypto Mining
$PBW — Clean Energy
$FDRV — EV & Future Transportation
$SOXX — Broad Semiconductors
$ARKK — ARK Innovation
$MEME — Meme Stocks
$UFO — Space Industry
$XSD — Equal-Weight Semiconductors
$SMH — Semiconductor Giants
$BAI — AI & Tech Active
$NASA — Space Economy

Weather markets on Polymarket are full of easy money - if you know whose trades to follow

Most people are just guessing on temperature outcomes while a small group of traders is consistently extracting edge using actual modeling and data

Here's exactly how to find them using Parity Terminal in under a minute

Open Parity Terminal → Live Trades tab → apply these filters:

• Market: Highest Temperature
• Side: BUY
• Exclude bots
• Price: 5c–95c
• PnL: >$5,000+
• Win rate: >80%
• Balance: >$1,000+

This gives you a clean, filtered list of profitable weather traders with no bots and no noise - just wallets with a proven track record

Bookmark their profiles, study their entry timing, and start building your own edge from theirs

predictparity.com

$BB

Most investors still think BlackBerry is a turnaround story.

The market is increasingly starting to realize it may actually be an AI infrastructure story.

Not because of chatbots.

Because of QNX.

QNX already powers critical systems across automotive, robotics, industrial automation and next-generation autonomous platforms.

While everyone focuses on AI models…

the real opportunity may be the software foundations enabling AI to operate safely in the physical world.

Cars.
Robots.
Industrial systems.
Autonomous machines.

The market is beginning to look at BlackBerry very differently.

And the chart is reflecting that shift.

EUROPE WANTS TO TAX YOU ON MONEY YOU NEVER MADE.

🇪🇺 The Netherlands: 36% on unrealized gains from 2028.
Your portfolio goes up on paper. You sell nothing. You receive no cash.
The government sends a bill anyway.

And the EU just proposed a 0.1% tax on every crypto transaction across the bloc. Up to €20 billion targeted through 2034.

One taxes the trade. The other taxes a gain you never took.

America writes rules to pull capital in.
Europe prices the exit before you reach the door.

2028 is coming. The smart money is already moving.

May '26 LLM list (final)

GPT-5.6 ❌
Claude Sonnet-4.8 ❌
Claude Mythos (official) ❌
Claude Opus-4.8 ✅
Gemini 3.5 Flash ✅
Gemini 3.1 Flash Lite ✅
Gemma 4 Family ✅
Grok 4.3 Official ✅
MiniMax M3 ❌
Kimi K3.0 ❌
Qwen3.6-Max (official) ❌
Qwen3.7-Max ✅
Qwen3.7-30B ❌ 🙏
Step 3.7 Flash ✅
Hunyuan3 MoE ❌
GLM-5.1 ✅
MiMo-V2.5 ✅
Ring-2.6-1T ✅
Ernie 5.1 ✅
ZAYA1-8B ✅
ZAYA1-74B-Preview ✅

BUILD 🔥: Exclusive, an early look at Copilot Code and Copilot Cowork tabs of the upcoming super app from Microsoft, following earlier leaked screenshot of the Scout 24/7 Agent.

Developers, Developers, Developers

copilot.com

Thanks to #VideoCardz leakpost, we now a little more about the new N1 family of NPUs to be announced next week.

🔑 Key specs from the leak:
✦ 20-core ARM CPU (Cortex-X925 + A725)
✦ 6144 CUDA cores (RTX 5070-level GPU)
✦ Up to 128GB LPDDR5X memory
✦ 45–80W TDP

🎯 This positions NVIDIA to compete directly with:
✦ AMD Strix Halo (Ryzen AI Max)
✦ Intel Razor Lake / Serpent Lake (upcoming ARM chips)

If true, this could be the strongest Windows on ARM platform combining CPU power with desktop-class NVIDIA graphics in one chip.

Chamath: AI advantage may come less from models than from private inputs.

"When labs can build similar models, the real win comes from one unique ingredient in order to monetize it well.

Here is a basic thing about machine learning that is worth knowing: if you take 1,000 of the same inputs and give them to Facebook, Microsoft, Google, and Amazon, they will all come up with the same machine learning model.

But if you have one extra thing, one little ingredient that all of those other companies do not have, your output can be markedly different.

It is like giving two great chefs three ingredients, but giving the third chef one extra ingredient. That person has the ability to do something very special.

Right now, we are in a world where everybody is crawling the open web. We are going to move to a world where, as everybody gets sophisticated enough and information is widely available, somebody is going to say, “You know what? This site, I am not going to allow anybody else to access. It is only for me, only for my models.” Those models will become better.

So we have to let that play out a little bit. It is going to be a really interesting arms race.

The next wave of M&A, for example, could be companies like Google, Microsoft, and Facebook looking at these companies and saying, “Can they be viable inputs to my large language models or to my other machine learning and AI models?”

---

A company with unique workflows, transactions, medical records, industrial logs, legal archives, design files, or user behavior can turn boring private data into a compounding advantage.

Some startups may never become great public companies on their own, yet still become valuable because they own a data stream that makes a larger AI system sharper, more differentiated, or harder to copy.

That turns acquisition strategy upside down: the buyer may not be purchasing revenue, brand, or even software, but a private ingredient for intelligence.